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// lat/lattice-functions.cc
// Copyright 2009-2011 Saarland University (Author: Arnab Ghoshal)
// 2012-2013 Johns Hopkins University (Author: Daniel Povey); Chao Weng;
// Bagher BabaAli
// 2013 Cisco Systems (author: Neha Agrawal) [code modified
// from original code in ../gmmbin/gmm-rescore-lattice.cc]
// 2014 Guoguo Chen
// See ../../COPYING for clarification regarding multiple authors
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
// WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
// MERCHANTABLITY OR NON-INFRINGEMENT.
// See the Apache 2 License for the specific language governing permissions and
// limitations under the License.
#include "lat/lattice-functions.h"
#include "hmm/transition-model.h"
#include "util/stl-utils.h"
#include "base/kaldi-math.h"
#include "hmm/hmm-utils.h"
namespace kaldi {
using std::map;
using std::vector;
void GetPerFrameAcousticCosts(const Lattice &nbest, Vector<BaseFloat> *per_frame_loglikes) {
using namespace fst;
typedef Lattice::Arc::Weight Weight;
vector<BaseFloat> loglikes;
int32 cur_state = nbest.Start();
int32 prev_frame = -1;
BaseFloat eps_acwt = 0.0;
while(1) {
Weight w = nbest.Final(cur_state);
if (w != Weight::Zero()) {
KALDI_ASSERT(nbest.NumArcs(cur_state) == 0);
if (per_frame_loglikes != NULL) {
SubVector<BaseFloat> subvec(&(loglikes[0]), loglikes.size());
Vector<BaseFloat> vec(subvec);
*per_frame_loglikes = vec;
}
break;
} else {
KALDI_ASSERT(nbest.NumArcs(cur_state) == 1);
fst::ArcIterator<Lattice> iter(nbest, cur_state);
const Lattice::Arc &arc = iter.Value();
BaseFloat acwt = arc.weight.Value2();
if (arc.ilabel != 0) {
if (eps_acwt > 0) {
acwt += eps_acwt;
eps_acwt = 0.0;
}
loglikes.push_back(acwt);
prev_frame++;
} else if (acwt == acwt){
if (prev_frame > -1) {
loglikes[prev_frame] += acwt;
} else {
eps_acwt += acwt;
}
}
cur_state = arc.nextstate;
}
}
}
int32 LatticeStateTimes(const Lattice &lat, vector<int32> *times) {
if (!lat.Properties(fst::kTopSorted, true))
KALDI_ERR << "Input lattice must be topologically sorted.";
KALDI_ASSERT(lat.Start() == 0);
int32 num_states = lat.NumStates();
times->clear();
times->resize(num_states, -1);
(*times)[0] = 0;
for (int32 state = 0; state < num_states; state++) {
int32 cur_time = (*times)[state];
for (fst::ArcIterator<Lattice> aiter(lat, state); !aiter.Done();
aiter.Next()) {
const LatticeArc &arc = aiter.Value();
if (arc.ilabel != 0) { // Non-epsilon input label on arc
// next time instance
if ((*times)[arc.nextstate] == -1) {
(*times)[arc.nextstate] = cur_time + 1;
} else {
KALDI_ASSERT((*times)[arc.nextstate] == cur_time + 1);
}
} else { // epsilon input label on arc
// Same time instance
if ((*times)[arc.nextstate] == -1)
(*times)[arc.nextstate] = cur_time;
else
KALDI_ASSERT((*times)[arc.nextstate] == cur_time);
}
}
}
return (*std::max_element(times->begin(), times->end()));
}
int32 CompactLatticeStateTimes(const CompactLattice &lat, vector<int32> *times) {
if (!lat.Properties(fst::kTopSorted, true))
KALDI_ERR << "Input lattice must be topologically sorted.";
KALDI_ASSERT(lat.Start() == 0);
int32 num_states = lat.NumStates();
times->clear();
times->resize(num_states, -1);
(*times)[0] = 0;
int32 utt_len = -1;
for (int32 state = 0; state < num_states; state++) {
int32 cur_time = (*times)[state];
for (fst::ArcIterator<CompactLattice> aiter(lat, state); !aiter.Done();
aiter.Next()) {
const CompactLatticeArc &arc = aiter.Value();
int32 arc_len = static_cast<int32>(arc.weight.String().size());
if ((*times)[arc.nextstate] == -1)
(*times)[arc.nextstate] = cur_time + arc_len;
else
KALDI_ASSERT((*times)[arc.nextstate] == cur_time + arc_len);
}
if (lat.Final(state) != CompactLatticeWeight::Zero()) {
int32 this_utt_len = (*times)[state] + lat.Final(state).String().size();
if (utt_len == -1) utt_len = this_utt_len;
else {
if (this_utt_len != utt_len) {
KALDI_WARN << "Utterance does not "
"seem to have a consistent length.";
utt_len = std::max(utt_len, this_utt_len);
}
}
}
}
if (utt_len == -1) {
KALDI_WARN << "Utterance does not have a final-state.";
return 0;
}
return utt_len;
}
bool ComputeCompactLatticeAlphas(const CompactLattice &clat,
vector<double> *alpha) {
using namespace fst;
// typedef the arc, weight types
typedef CompactLattice::Arc Arc;
typedef Arc::Weight Weight;
typedef Arc::StateId StateId;
//Make sure the lattice is topologically sorted.
if (clat.Properties(fst::kTopSorted, true) == 0) {
KALDI_WARN << "Input lattice must be topologically sorted.";
return false;
}
if (clat.Start() != 0) {
KALDI_WARN << "Input lattice must start from state 0.";
return false;
}
int32 num_states = clat.NumStates();
(*alpha).resize(0);
(*alpha).resize(num_states, kLogZeroDouble);
// Now propagate alphas forward. Note that we don't acount the weight of the
// final state to alpha[final_state] -- we acount it to beta[final_state];
(*alpha)[0] = 0.0;
for (StateId s = 0; s < num_states; s++) {
double this_alpha = (*alpha)[s];
for (ArcIterator<CompactLattice> aiter(clat, s); !aiter.Done(); aiter.Next()) {
const Arc &arc = aiter.Value();
double arc_like = -(arc.weight.Weight().Value1() + arc.weight.Weight().Value2());
(*alpha)[arc.nextstate] = LogAdd((*alpha)[arc.nextstate], this_alpha + arc_like);
}
}
return true;
}
bool ComputeCompactLatticeBetas(const CompactLattice &clat,
vector<double> *beta) {
using namespace fst;
// typedef the arc, weight types
typedef CompactLattice::Arc Arc;
typedef Arc::Weight Weight;
typedef Arc::StateId StateId;
// Make sure the lattice is topologically sorted.
if (clat.Properties(fst::kTopSorted, true) == 0) {
KALDI_WARN << "Input lattice must be topologically sorted.";
return false;
}
if (clat.Start() != 0) {
KALDI_WARN << "Input lattice must start from state 0.";
return false;
}
int32 num_states = clat.NumStates();
(*beta).resize(0);
(*beta).resize(num_states, kLogZeroDouble);
// Now propagate betas backward. Note that beta[final_state] contains the
// weight of the final state in the lattice -- compare that with alpha.
for (StateId s = num_states-1; s >= 0; s--) {
Weight f = clat.Final(s);
double this_beta = -(f.Weight().Value1()+f.Weight().Value2());
for (ArcIterator<CompactLattice> aiter(clat, s); !aiter.Done(); aiter.Next()) {
const Arc &arc = aiter.Value();
double arc_like = -(arc.weight.Weight().Value1()+arc.weight.Weight().Value2());
double arc_beta = (*beta)[arc.nextstate] + arc_like;
this_beta = LogAdd(this_beta, arc_beta);
}
(*beta)[s] = this_beta;
}
return true;
}
template<class LatType> // could be Lattice or CompactLattice
bool PruneLattice(BaseFloat beam, LatType *lat) {
typedef typename LatType::Arc Arc;
typedef typename Arc::Weight Weight;
typedef typename Arc::StateId StateId;
KALDI_ASSERT(beam > 0.0);
if (!lat->Properties(fst::kTopSorted, true)) {
if (fst::TopSort(lat) == false) {
KALDI_WARN << "Cycles detected in lattice";
return false;
}
}
// We assume states before "start" are not reachable, since
// the lattice is topologically sorted.
int32 start = lat->Start();
int32 num_states = lat->NumStates();
if (num_states == 0) return false;
std::vector<double> forward_cost(num_states,
std::numeric_limits<double>::infinity()); // viterbi forward.
forward_cost[start] = 0.0; // lattice can't have cycles so couldn't be
// less than this.
double best_final_cost = std::numeric_limits<double>::infinity();
// Update the forward probs.
// Thanks to Jing Zheng for finding a bug here.
for (int32 state = 0; state < num_states; state++) {
double this_forward_cost = forward_cost[state];
for (fst::ArcIterator<LatType> aiter(*lat, state);
!aiter.Done();
aiter.Next()) {
const Arc &arc(aiter.Value());
StateId nextstate = arc.nextstate;
KALDI_ASSERT(nextstate > state && nextstate < num_states);
double next_forward_cost = this_forward_cost +
ConvertToCost(arc.weight);
if (forward_cost[nextstate] > next_forward_cost)
forward_cost[nextstate] = next_forward_cost;
}
Weight final_weight = lat->Final(state);
double this_final_cost = this_forward_cost +
ConvertToCost(final_weight);
if (this_final_cost < best_final_cost)
best_final_cost = this_final_cost;
}
int32 bad_state = lat->AddState(); // this state is not final.
double cutoff = best_final_cost + beam;
// Go backwards updating the backward probs (which share memory with the
// forward probs), and pruning arcs and deleting final-probs. We prune arcs
// by making them point to the non-final state "bad_state". We'll then use
// Trim() to remove unnecessary arcs and states. [this is just easier than
// doing it ourselves.]
std::vector<double> &backward_cost(forward_cost);
for (int32 state = num_states - 1; state >= 0; state--) {
double this_forward_cost = forward_cost[state];
double this_backward_cost = ConvertToCost(lat->Final(state));
if (this_backward_cost + this_forward_cost > cutoff
&& this_backward_cost != std::numeric_limits<double>::infinity())
lat->SetFinal(state, Weight::Zero());
for (fst::MutableArcIterator<LatType> aiter(lat, state);
!aiter.Done();
aiter.Next()) {
Arc arc(aiter.Value());
StateId nextstate = arc.nextstate;
KALDI_ASSERT(nextstate > state && nextstate < num_states);
double arc_cost = ConvertToCost(arc.weight),
arc_backward_cost = arc_cost + backward_cost[nextstate],
this_fb_cost = this_forward_cost + arc_backward_cost;
if (arc_backward_cost < this_backward_cost)
this_backward_cost = arc_backward_cost;
if (this_fb_cost > cutoff) { // Prune the arc.
arc.nextstate = bad_state;
aiter.SetValue(arc);
}
}
backward_cost[state] = this_backward_cost;
}
fst::Connect(lat);
return (lat->NumStates() > 0);
}
// instantiate the template for lattice and CompactLattice.
template bool PruneLattice(BaseFloat beam, Lattice *lat);
template bool PruneLattice(BaseFloat beam, CompactLattice *lat);
BaseFloat LatticeForwardBackward(const Lattice &lat, Posterior *post,
double *acoustic_like_sum) {
// Note, Posterior is defined as follows: Indexed [frame], then a list
// of (transition-id, posterior-probability) pairs.
// typedef std::vector<std::vector<std::pair<int32, BaseFloat> > > Posterior;
using namespace fst;
typedef Lattice::Arc Arc;
typedef Arc::Weight Weight;
typedef Arc::StateId StateId;
if (acoustic_like_sum) *acoustic_like_sum = 0.0;
// Make sure the lattice is topologically sorted.
if (lat.Properties(fst::kTopSorted, true) == 0)
KALDI_ERR << "Input lattice must be topologically sorted.";
KALDI_ASSERT(lat.Start() == 0);
int32 num_states = lat.NumStates();
vector<int32> state_times;
int32 max_time = LatticeStateTimes(lat, &state_times);
std::vector<double> alpha(num_states, kLogZeroDouble);
std::vector<double> &beta(alpha); // we re-use the same memory for
// this, but it's semantically distinct so we name it differently.
double tot_forward_prob = kLogZeroDouble;
post->clear();
post->resize(max_time);
alpha[0] = 0.0;
// Propagate alphas forward.
for (StateId s = 0; s < num_states; s++) {
double this_alpha = alpha[s];
for (ArcIterator<Lattice> aiter(lat, s); !aiter.Done(); aiter.Next()) {
const Arc &arc = aiter.Value();
double arc_like = -ConvertToCost(arc.weight);
alpha[arc.nextstate] = LogAdd(alpha[arc.nextstate], this_alpha + arc_like);
}
Weight f = lat.Final(s);
if (f != Weight::Zero()) {
double final_like = this_alpha - (f.Value1() + f.Value2());
tot_forward_prob = LogAdd(tot_forward_prob, final_like);
KALDI_ASSERT(state_times[s] == max_time &&
"Lattice is inconsistent (final-prob not at max_time)");
}
}
for (StateId s = num_states-1; s >= 0; s--) {
Weight f = lat.Final(s);
double this_beta = -(f.Value1() + f.Value2());
for (ArcIterator<Lattice> aiter(lat, s); !aiter.Done(); aiter.Next()) {
const Arc &arc = aiter.Value();
double arc_like = -ConvertToCost(arc.weight),
arc_beta = beta[arc.nextstate] + arc_like;
this_beta = LogAdd(this_beta, arc_beta);
int32 transition_id = arc.ilabel;
// The following "if" is an optimization to avoid un-needed exp().
if (transition_id != 0 || acoustic_like_sum != NULL) {
double posterior = Exp(alpha[s] + arc_beta - tot_forward_prob);
if (transition_id != 0) // Arc has a transition-id on it [not epsilon]
(*post)[state_times[s]].push_back(std::make_pair(transition_id,
static_cast<kaldi::BaseFloat>(posterior)));
if (acoustic_like_sum != NULL)
*acoustic_like_sum -= posterior * arc.weight.Value2();
}
}
if (acoustic_like_sum != NULL && f != Weight::Zero()) {
double final_logprob = - ConvertToCost(f),
posterior = Exp(alpha[s] + final_logprob - tot_forward_prob);
*acoustic_like_sum -= posterior * f.Value2();
}
beta[s] = this_beta;
}
double tot_backward_prob = beta[0];
if (!ApproxEqual(tot_forward_prob, tot_backward_prob, 1e-8)) {
KALDI_WARN << "Total forward probability over lattice = " << tot_forward_prob
<< ", while total backward probability = " << tot_backward_prob;
}
// Now combine any posteriors with the same transition-id.
for (int32 t = 0; t < max_time; t++)
MergePairVectorSumming(&((*post)[t]));
return tot_backward_prob;
}
void LatticeActivePhones(const Lattice &lat, const TransitionModel &trans,
const vector<int32> &silence_phones,
vector< std::set<int32> > *active_phones) {
KALDI_ASSERT(IsSortedAndUniq(silence_phones));
vector<int32> state_times;
int32 num_states = lat.NumStates();
int32 max_time = LatticeStateTimes(lat, &state_times);
active_phones->clear();
active_phones->resize(max_time);
for (int32 state = 0; state < num_states; state++) {
int32 cur_time = state_times[state];
for (fst::ArcIterator<Lattice> aiter(lat, state); !aiter.Done();
aiter.Next()) {
const LatticeArc &arc = aiter.Value();
if (arc.ilabel != 0) { // Non-epsilon arc
int32 phone = trans.TransitionIdToPhone(arc.ilabel);
if (!std::binary_search(silence_phones.begin(),
silence_phones.end(), phone))
(*active_phones)[cur_time].insert(phone);
}
} // end looping over arcs
} // end looping over states
}
void ConvertLatticeToPhones(const TransitionModel &trans,
Lattice *lat) {
typedef LatticeArc Arc;
int32 num_states = lat->NumStates();
for (int32 state = 0; state < num_states; state++) {
for (fst::MutableArcIterator<Lattice> aiter(lat, state); !aiter.Done();
aiter.Next()) {
Arc arc(aiter.Value());
arc.olabel = 0; // remove any word.
if ((arc.ilabel != 0) // has a transition-id on input..
&& (trans.TransitionIdToHmmState(arc.ilabel) == 0)
&& (!trans.IsSelfLoop(arc.ilabel))) {
// && trans.IsFinal(arc.ilabel)) // there is one of these per phone...
arc.olabel = trans.TransitionIdToPhone(arc.ilabel);
}
aiter.SetValue(arc);
} // end looping over arcs
} // end looping over states
}
static inline double LogAddOrMax(bool viterbi, double a, double b) {
if (viterbi)
return std::max(a, b);
else
return LogAdd(a, b);
}
template<typename LatticeType>
double ComputeLatticeAlphasAndBetas(const LatticeType &lat,
bool viterbi,
vector<double> *alpha,
vector<double> *beta) {
typedef typename LatticeType::Arc Arc;
typedef typename Arc::Weight Weight;
typedef typename Arc::StateId StateId;
StateId num_states = lat.NumStates();
KALDI_ASSERT(lat.Properties(fst::kTopSorted, true) == fst::kTopSorted);
KALDI_ASSERT(lat.Start() == 0);
alpha->clear();
beta->clear();
alpha->resize(num_states, kLogZeroDouble);
beta->resize(num_states, kLogZeroDouble);
double tot_forward_prob = kLogZeroDouble;
(*alpha)[0] = 0.0;
// Propagate alphas forward.
for (StateId s = 0; s < num_states; s++) {
double this_alpha = (*alpha)[s];
for (fst::ArcIterator<LatticeType> aiter(lat, s); !aiter.Done();
aiter.Next()) {
const Arc &arc = aiter.Value();
double arc_like = -ConvertToCost(arc.weight);
(*alpha)[arc.nextstate] = LogAddOrMax(viterbi, (*alpha)[arc.nextstate],
this_alpha + arc_like);
}
Weight f = lat.Final(s);
if (f != Weight::Zero()) {
double final_like = this_alpha - ConvertToCost(f);
tot_forward_prob = LogAddOrMax(viterbi, tot_forward_prob, final_like);
}
}
for (StateId s = num_states-1; s >= 0; s--) { // it's guaranteed signed.
double this_beta = -ConvertToCost(lat.Final(s));
for (fst::ArcIterator<LatticeType> aiter(lat, s); !aiter.Done();
aiter.Next()) {
const Arc &arc = aiter.Value();
double arc_like = -ConvertToCost(arc.weight),
arc_beta = (*beta)[arc.nextstate] + arc_like;
this_beta = LogAddOrMax(viterbi, this_beta, arc_beta);
}
(*beta)[s] = this_beta;
}
double tot_backward_prob = (*beta)[lat.Start()];
if (!ApproxEqual(tot_forward_prob, tot_backward_prob, 1e-8)) {
KALDI_WARN << "Total forward probability over lattice = " << tot_forward_prob
<< ", while total backward probability = " << tot_backward_prob;
}
// Split the difference when returning... they should be the same.
return 0.5 * (tot_backward_prob + tot_forward_prob);
}
// instantiate the template for Lattice and CompactLattice
template
double ComputeLatticeAlphasAndBetas(const Lattice &lat,
bool viterbi,
vector<double> *alpha,
vector<double> *beta);
template
double ComputeLatticeAlphasAndBetas(const CompactLattice &lat,
bool viterbi,
vector<double> *alpha,
vector<double> *beta);
/// This is used in CompactLatticeLimitDepth.
struct LatticeArcRecord {
BaseFloat logprob; // logprob <= 0 is the best Viterbi logprob of this arc,
// minus the overall best-cost of the lattice.
CompactLatticeArc::StateId state; // state in the lattice.
size_t arc; // arc index within the state.
bool operator < (const LatticeArcRecord &other) const {
return logprob < other.logprob;
}
};
void CompactLatticeLimitDepth(int32 max_depth_per_frame,
CompactLattice *clat) {
typedef CompactLatticeArc Arc;
typedef Arc::Weight Weight;
typedef Arc::StateId StateId;
if (clat->Start() == fst::kNoStateId) {
KALDI_WARN << "Limiting depth of empty lattice.";
return;
}
if (clat->Properties(fst::kTopSorted, true) == 0) {
if (!TopSort(clat))
KALDI_ERR << "Topological sorting of lattice failed.";
}
vector<int32> state_times;
int32 T = CompactLatticeStateTimes(*clat, &state_times);
// The alpha and beta quantities here are "viterbi" alphas and beta.
std::vector<double> alpha;
std::vector<double> beta;
bool viterbi = true;
double best_prob = ComputeLatticeAlphasAndBetas(*clat, viterbi,
&alpha, &beta);
std::vector<std::vector<LatticeArcRecord> > arc_records(T);
StateId num_states = clat->NumStates();
for (StateId s = 0; s < num_states; s++) {
for (fst::ArcIterator<CompactLattice> aiter(*clat, s); !aiter.Done();
aiter.Next()) {
const Arc &arc = aiter.Value();
LatticeArcRecord arc_record;
arc_record.state = s;
arc_record.arc = aiter.Position();
arc_record.logprob =
(alpha[s] + beta[arc.nextstate] - ConvertToCost(arc.weight))
- best_prob;
KALDI_ASSERT(arc_record.logprob < 0.1); // Should be zero or negative.
int32 num_frames = arc.weight.String().size(), start_t = state_times[s];
for (int32 t = start_t; t < start_t + num_frames; t++) {
KALDI_ASSERT(t < T);
arc_records[t].push_back(arc_record);
}
}
}
StateId dead_state = clat->AddState(); // A non-coaccesible state which we use
// to remove arcs (make them end
// there).
size_t max_depth = max_depth_per_frame;
for (int32 t = 0; t < T; t++) {
size_t size = arc_records[t].size();
if (size > max_depth) {
// we sort from worst to best, so we keep the later-numbered ones,
// and delete the lower-numbered ones.
size_t cutoff = size - max_depth;
std::nth_element(arc_records[t].begin(),
arc_records[t].begin() + cutoff,
arc_records[t].end());
for (size_t index = 0; index < cutoff; index++) {
LatticeArcRecord record(arc_records[t][index]);
fst::MutableArcIterator<CompactLattice> aiter(clat, record.state);
aiter.Seek(record.arc);
Arc arc = aiter.Value();
if (arc.nextstate != dead_state) { // not already killed.
arc.nextstate = dead_state;
aiter.SetValue(arc);
}
}
}
}
Connect(clat);
TopSortCompactLatticeIfNeeded(clat);
}
void TopSortCompactLatticeIfNeeded(CompactLattice *clat) {
if (clat->Properties(fst::kTopSorted, true) == 0) {
if (fst::TopSort(clat) == false) {
KALDI_ERR << "Topological sorting failed";
}
}
}
void TopSortLatticeIfNeeded(Lattice *lat) {
if (lat->Properties(fst::kTopSorted, true) == 0) {
if (fst::TopSort(lat) == false) {
KALDI_ERR << "Topological sorting failed";
}
}
}
/// Returns the depth of the lattice, defined as the average number of
/// arcs crossing any given frame. Returns 1 for empty lattices.
/// Requires that input is topologically sorted.
BaseFloat CompactLatticeDepth(const CompactLattice &clat,
int32 *num_frames) {
typedef CompactLattice::Arc::StateId StateId;
if (clat.Properties(fst::kTopSorted, true) == 0) {
KALDI_ERR << "Lattice input to CompactLatticeDepth was not topologically "
<< "sorted.";
}
if (clat.Start() == fst::kNoStateId) {
*num_frames = 0;
return 1.0;
}
size_t num_arc_frames = 0;
int32 t;
{
vector<int32> state_times;
t = CompactLatticeStateTimes(clat, &state_times);
}
if (num_frames != NULL)
*num_frames = t;
for (StateId s = 0; s < clat.NumStates(); s++) {
for (fst::ArcIterator<CompactLattice> aiter(clat, s); !aiter.Done();
aiter.Next()) {
const CompactLatticeArc &arc = aiter.Value();
num_arc_frames += arc.weight.String().size();
}
num_arc_frames += clat.Final(s).String().size();
}
return num_arc_frames / static_cast<BaseFloat>(t);
}
void CompactLatticeDepthPerFrame(const CompactLattice &clat,
std::vector<int32> *depth_per_frame) {
typedef CompactLattice::Arc::StateId StateId;
if (clat.Properties(fst::kTopSorted, true) == 0) {
KALDI_ERR << "Lattice input to CompactLatticeDepthPerFrame was not "
<< "topologically sorted.";
}
if (clat.Start() == fst::kNoStateId) {
depth_per_frame->clear();
return;
}
vector<int32> state_times;
int32 T = CompactLatticeStateTimes(clat, &state_times);
depth_per_frame->clear();
if (T <= 0) {
return;
} else {
depth_per_frame->resize(T, 0);
for (StateId s = 0; s < clat.NumStates(); s++) {
int32 start_time = state_times[s];
for (fst::ArcIterator<CompactLattice> aiter(clat, s); !aiter.Done();
aiter.Next()) {
const CompactLatticeArc &arc = aiter.Value();
int32 len = arc.weight.String().size();
for (int32 t = start_time; t < start_time + len; t++) {
KALDI_ASSERT(t < T);
(*depth_per_frame)[t]++;
}
}
int32 final_len = clat.Final(s).String().size();
for (int32 t = start_time; t < start_time + final_len; t++) {
KALDI_ASSERT(t < T);
(*depth_per_frame)[t]++;
}
}
}
}
void ConvertCompactLatticeToPhones(const TransitionModel &trans,
CompactLattice *clat) {
typedef CompactLatticeArc Arc;
typedef Arc::Weight Weight;
int32 num_states = clat->NumStates();
for (int32 state = 0; state < num_states; state++) {
for (fst::MutableArcIterator<CompactLattice> aiter(clat, state);
!aiter.Done();
aiter.Next()) {
Arc arc(aiter.Value());
std::vector<int32> phone_seq;
const std::vector<int32> &tid_seq = arc.weight.String();
for (std::vector<int32>::const_iterator iter = tid_seq.begin();
iter != tid_seq.end(); ++iter) {
if (trans.IsFinal(*iter))// note: there is one of these per phone...
phone_seq.push_back(trans.TransitionIdToPhone(*iter));
}
arc.weight.SetString(phone_seq);
aiter.SetValue(arc);
} // end looping over arcs
Weight f = clat->Final(state);
if (f != Weight::Zero()) {
std::vector<int32> phone_seq;
const std::vector<int32> &tid_seq = f.String();
for (std::vector<int32>::const_iterator iter = tid_seq.begin();
iter != tid_seq.end(); ++iter) {
if (trans.IsFinal(*iter))// note: there is one of these per phone...
phone_seq.push_back(trans.TransitionIdToPhone(*iter));
}
f.SetString(phone_seq);
clat->SetFinal(state, f);
}
} // end looping over states
}
bool LatticeBoost(const TransitionModel &trans,
const std::vector<int32> &alignment,
const std::vector<int32> &silence_phones,
BaseFloat b,
BaseFloat max_silence_error,
Lattice *lat) {
TopSortLatticeIfNeeded(lat);
// get all stored properties (test==false means don't test if not known).
uint64 props = lat->Properties(fst::kFstProperties,
false);
KALDI_ASSERT(IsSortedAndUniq(silence_phones));
KALDI_ASSERT(max_silence_error >= 0.0 && max_silence_error <= 1.0);
vector<int32> state_times;
int32 num_states = lat->NumStates();
int32 num_frames = LatticeStateTimes(*lat, &state_times);
KALDI_ASSERT(num_frames == static_cast<int32>(alignment.size()));
for (int32 state = 0; state < num_states; state++) {
int32 cur_time = state_times[state];
for (fst::MutableArcIterator<Lattice> aiter(lat, state); !aiter.Done();
aiter.Next()) {
LatticeArc arc = aiter.Value();
if (arc.ilabel != 0) { // Non-epsilon arc
if (arc.ilabel < 0 || arc.ilabel > trans.NumTransitionIds()) {
KALDI_WARN << "Lattice has out-of-range transition-ids: "
<< "lattice/model mismatch?";
return false;
}
int32 phone = trans.TransitionIdToPhone(arc.ilabel),
ref_phone = trans.TransitionIdToPhone(alignment[cur_time]);
BaseFloat frame_error;
if (phone == ref_phone) {
frame_error = 0.0;
} else { // an error...
if (std::binary_search(silence_phones.begin(), silence_phones.end(), phone))
frame_error = max_silence_error;
else
frame_error = 1.0;
}
BaseFloat delta_cost = -b * frame_error; // negative cost if
// frame is wrong, to boost likelihood of arcs with errors on them.
// Add this cost to the graph part.
arc.weight.SetValue1(arc.weight.Value1() + delta_cost);
aiter.SetValue(arc);
}
}
}
// All we changed is the weights, so any properties that were
// known before, are still known, except for whether or not the
// lattice was weighted.
lat->SetProperties(props,
~(fst::kWeighted|fst::kUnweighted));
return true;
}
BaseFloat LatticeForwardBackwardMpeVariants(
const TransitionModel &trans,
const std::vector<int32> &silence_phones,
const Lattice &lat,
const std::vector<int32> &num_ali,
std::string criterion,
bool one_silence_class,
Posterior *post) {
using namespace fst;
typedef Lattice::Arc Arc;
typedef Arc::Weight Weight;
typedef Arc::StateId StateId;
KALDI_ASSERT(criterion == "mpfe" || criterion == "smbr");
bool is_mpfe = (criterion == "mpfe");
if (lat.Properties(fst::kTopSorted, true) == 0)
KALDI_ERR << "Input lattice must be topologically sorted.";
KALDI_ASSERT(lat.Start() == 0);
int32 num_states = lat.NumStates();
vector<int32> state_times;
int32 max_time = LatticeStateTimes(lat, &state_times);
KALDI_ASSERT(max_time == static_cast<int32>(num_ali.size()));
std::vector<double> alpha(num_states, kLogZeroDouble),
alpha_smbr(num_states, 0), //forward variable for sMBR
beta(num_states, kLogZeroDouble),
beta_smbr(num_states, 0); //backward variable for sMBR
double tot_forward_prob = kLogZeroDouble;
double tot_forward_score = 0;
post->clear();
post->resize(max_time);
alpha[0] = 0.0;
// First Pass Forward,
for (StateId s = 0; s < num_states; s++) {
double this_alpha = alpha[s];
for (ArcIterator<Lattice> aiter(lat, s); !aiter.Done(); aiter.Next()) {
const Arc &arc = aiter.Value();
double arc_like = -ConvertToCost(arc.weight);
alpha[arc.nextstate] = LogAdd(alpha[arc.nextstate], this_alpha + arc_like);
}
Weight f = lat.Final(s);
if (f != Weight::Zero()) {
double final_like = this_alpha - (f.Value1() + f.Value2());
tot_forward_prob = LogAdd(tot_forward_prob, final_like);
KALDI_ASSERT(state_times[s] == max_time &&
"Lattice is inconsistent (final-prob not at max_time)");
}
}
// First Pass Backward,
for (StateId s = num_states-1; s >= 0; s--) {
Weight f = lat.Final(s);
double this_beta = -(f.Value1() + f.Value2());
for (ArcIterator<Lattice> aiter(lat, s); !aiter.Done(); aiter.Next()) {
const Arc &arc = aiter.Value();
double arc_like = -ConvertToCost(arc.weight),
arc_beta = beta[arc.nextstate] + arc_like;
this_beta = LogAdd(this_beta, arc_beta);
}
beta[s] = this_beta;
}
// First Pass Forward-Backward Check
double tot_backward_prob = beta[0];
// may loose the condition somehow here 1e-6 (was 1e-8)
if (!ApproxEqual(tot_forward_prob, tot_backward_prob, 1e-6)) {
KALDI_ERR << "Total forward probability over lattice = " << tot_forward_prob
<< ", while total backward probability = " << tot_backward_prob;
}
alpha_smbr[0] = 0.0;
// Second Pass Forward, calculate forward for MPFE/SMBR
for (StateId s = 0; s < num_states; s++) {
double this_alpha = alpha[s];
for (ArcIterator<Lattice> aiter(lat, s); !aiter.Done(); aiter.Next()) {
const Arc &arc = aiter.Value();
double arc_like = -ConvertToCost(arc.weight);
double frame_acc = 0.0;
if (arc.ilabel != 0) {
int32 cur_time = state_times[s];
int32 phone = trans.TransitionIdToPhone(arc.ilabel),
ref_phone = trans.TransitionIdToPhone(num_ali[cur_time]);
bool phone_is_sil = std::binary_search(silence_phones.begin(),
silence_phones.end(),
phone),
ref_phone_is_sil = std::binary_search(silence_phones.begin(),
silence_phones.end(),
ref_phone),
both_sil = phone_is_sil && ref_phone_is_sil;
if (!is_mpfe) { // smbr.
int32 pdf = trans.TransitionIdToPdf(arc.ilabel),
ref_pdf = trans.TransitionIdToPdf(num_ali[cur_time]);
if (!one_silence_class) // old behavior
frame_acc = (pdf == ref_pdf && !phone_is_sil) ? 1.0 : 0.0;
else
frame_acc = (pdf == ref_pdf || both_sil) ? 1.0 : 0.0;
} else {
if (!one_silence_class) // old behavior
frame_acc = (phone == ref_phone && !phone_is_sil) ? 1.0 : 0.0;
else
frame_acc = (phone == ref_phone || both_sil) ? 1.0 : 0.0;
}
}
double arc_scale = Exp(alpha[s] + arc_like - alpha[arc.nextstate]);
alpha_smbr[arc.nextstate] += arc_scale * (alpha_smbr[s] + frame_acc);
}
Weight f = lat.Final(s);
if (f != Weight::Zero()) {
double final_like = this_alpha - (f.Value1() + f.Value2());
double arc_scale = Exp(final_like - tot_forward_prob);
tot_forward_score += arc_scale * alpha_smbr[s];
KALDI_ASSERT(state_times[s] == max_time &&
"Lattice is inconsistent (final-prob not at max_time)");
}
}
// Second Pass Backward, collect Mpe style posteriors
for (StateId s = num_states-1; s >= 0; s--) {
for (ArcIterator<Lattice> aiter(lat, s); !aiter.Done(); aiter.Next()) {
const Arc &arc = aiter.Value();
double arc_like = -ConvertToCost(arc.weight),
arc_beta = beta[arc.nextstate] + arc_like;
double frame_acc = 0.0;
int32 transition_id = arc.ilabel;
if (arc.ilabel != 0) {
int32 cur_time = state_times[s];
int32 phone = trans.TransitionIdToPhone(arc.ilabel),
ref_phone = trans.TransitionIdToPhone(num_ali[cur_time]);
bool phone_is_sil = std::binary_search(silence_phones.begin(),
silence_phones.end(), phone),
ref_phone_is_sil = std::binary_search(silence_phones.begin(),
silence_phones.end(),
ref_phone),
both_sil = phone_is_sil && ref_phone_is_sil;
if (!is_mpfe) { // smbr.
int32 pdf = trans.TransitionIdToPdf(arc.ilabel),
ref_pdf = trans.TransitionIdToPdf(num_ali[cur_time]);
if (!one_silence_class) // old behavior
frame_acc = (pdf == ref_pdf && !phone_is_sil) ? 1.0 : 0.0;
else
frame_acc = (pdf == ref_pdf || both_sil) ? 1.0 : 0.0;
} else {
if (!one_silence_class) // old behavior
frame_acc = (phone == ref_phone && !phone_is_sil) ? 1.0 : 0.0;
else
frame_acc = (phone == ref_phone || both_sil) ? 1.0 : 0.0;
}
}
double arc_scale = Exp(beta[arc.nextstate] + arc_like - beta[s]);
// check arc_scale NAN,
// this is to prevent partial paths in Lattices
// i.e., paths don't survive to the final state
if (KALDI_ISNAN(arc_scale)) arc_scale = 0;
beta_smbr[s] += arc_scale * (beta_smbr[arc.nextstate] + frame_acc);
if (transition_id != 0) { // Arc has a transition-id on it [not epsilon]
double posterior = Exp(alpha[s] + arc_beta - tot_forward_prob);
double acc_diff = alpha_smbr[s] + frame_acc + beta_smbr[arc.nextstate]
- tot_forward_score;
double posterior_smbr = posterior * acc_diff;
(*post)[state_times[s]].push_back(std::make_pair(transition_id,
static_cast<BaseFloat>(posterior_smbr)));
}
}
}
//Second Pass Forward Backward check
double tot_backward_score = beta_smbr[0]; // Initial state id == 0
// may loose the condition somehow here 1e-5/1e-4
if (!ApproxEqual(tot_forward_score, tot_backward_score, 1e-4)) {
KALDI_ERR << "Total forward score over lattice = " << tot_forward_score
<< ", while total backward score = " << tot_backward_score;
}
// Output the computed posteriors
for (int32 t = 0; t < max_time; t++)
MergePairVectorSumming(&((*post)[t]));
return tot_forward_score;
}
bool CompactLatticeToWordAlignment(const CompactLattice &clat,
std::vector<int32> *words,
std::vector<int32> *begin_times,
std::vector<int32> *lengths) {
words->clear();
begin_times->clear();
lengths->clear();
typedef CompactLattice::Arc Arc;
typedef Arc::Label Label;
typedef CompactLattice::StateId StateId;
typedef CompactLattice::Weight Weight;
using namespace fst;
StateId state = clat.Start();
int32 cur_time = 0;
if (state == kNoStateId) {
KALDI_WARN << "Empty lattice.";
return false;
}
while (1) {
Weight final = clat.Final(state);
size_t num_arcs = clat.NumArcs(state);
if (final != Weight::Zero()) {
if (num_arcs != 0) {
KALDI_WARN << "Lattice is not linear.";
return false;
}
if (! final.String().empty()) {
KALDI_WARN << "Lattice has alignments on final-weight: probably "
"was not word-aligned (alignments will be approximate)";
}
return true;
} else {
if (num_arcs != 1) {
KALDI_WARN << "Lattice is not linear: num-arcs = " << num_arcs;
return false;
}
fst::ArcIterator<CompactLattice> aiter(clat, state);
const Arc &arc = aiter.Value();
Label word_id = arc.ilabel; // Note: ilabel==olabel, since acceptor.
// Also note: word_id may be zero; we output it anyway.
int32 length = arc.weight.String().size();
words->push_back(word_id);
begin_times->push_back(cur_time);
lengths->push_back(length);
cur_time += length;
state = arc.nextstate;
}
}
}
bool CompactLatticeToWordProns(
const TransitionModel &tmodel,
const CompactLattice &clat,
std::vector<int32> *words,
std::vector<int32> *begin_times,
std::vector<int32> *lengths,
std::vector<std::vector<int32> > *prons,
std::vector<std::vector<int32> > *phone_lengths) {
words->clear();
begin_times->clear();
lengths->clear();
prons->clear();
phone_lengths->clear();
typedef CompactLattice::Arc Arc;
typedef Arc::Label Label;
typedef CompactLattice::StateId StateId;
typedef CompactLattice::Weight Weight;
using namespace fst;
StateId state = clat.Start();
int32 cur_time = 0;
if (state == kNoStateId) {
KALDI_WARN << "Empty lattice.";
return false;
}
while (1) {
Weight final = clat.Final(state);
size_t num_arcs = clat.NumArcs(state);
if (final != Weight::Zero()) {
if (num_arcs != 0) {
KALDI_WARN << "Lattice is not linear.";
return false;
}
if (! final.String().empty()) {
KALDI_WARN << "Lattice has alignments on final-weight: probably "
"was not word-aligned (alignments will be approximate)";
}
return true;
} else {
if (num_arcs != 1) {
KALDI_WARN << "Lattice is not linear: num-arcs = " << num_arcs;
return false;
}
fst::ArcIterator<CompactLattice> aiter(clat, state);
const Arc &arc = aiter.Value();
Label word_id = arc.ilabel; // Note: ilabel==olabel, since acceptor.
// Also note: word_id may be zero; we output it anyway.
int32 length = arc.weight.String().size();
words->push_back(word_id);
begin_times->push_back(cur_time);
lengths->push_back(length);
const std::vector<int32> &arc_alignment = arc.weight.String();
std::vector<std::vector<int32> > split_alignment;
SplitToPhones(tmodel, arc_alignment, &split_alignment);
std::vector<int32> phones(split_alignment.size());
std::vector<int32> plengths(split_alignment.size());
for (size_t i = 0; i < split_alignment.size(); i++) {
KALDI_ASSERT(!split_alignment[i].empty());
phones[i] = tmodel.TransitionIdToPhone(split_alignment[i][0]);
plengths[i] = split_alignment[i].size();
}
prons->push_back(phones);
phone_lengths->push_back(plengths);
cur_time += length;
state = arc.nextstate;
}
}
}
void CompactLatticeShortestPath(const CompactLattice &clat,
CompactLattice *shortest_path) {
using namespace fst;
if (clat.Properties(fst::kTopSorted, true) == 0) {
CompactLattice clat_copy(clat);
if (!TopSort(&clat_copy))
KALDI_ERR << "Was not able to topologically sort lattice (cycles found?)";
CompactLatticeShortestPath(clat_copy, shortest_path);
return;
}
// Now we can assume it's topologically sorted.
shortest_path->DeleteStates();
if (clat.Start() == kNoStateId) return;
KALDI_ASSERT(clat.Start() == 0); // since top-sorted.
typedef CompactLatticeArc Arc;
typedef Arc::StateId StateId;
typedef CompactLatticeWeight Weight;
vector<std::pair<double, StateId> > best_cost_and_pred(clat.NumStates() + 1);
StateId superfinal = clat.NumStates();
for (StateId s = 0; s <= clat.NumStates(); s++) {
best_cost_and_pred[s].first = numeric_limits<double>::infinity();
best_cost_and_pred[s].second = fst::kNoStateId;
}
best_cost_and_pred[0].first = 0;
for (StateId s = 0; s < clat.NumStates(); s++) {
double my_cost = best_cost_and_pred[s].first;
for (ArcIterator<CompactLattice> aiter(clat, s);
!aiter.Done();
aiter.Next()) {
const Arc &arc = aiter.Value();
double arc_cost = ConvertToCost(arc.weight),
next_cost = my_cost + arc_cost;
if (next_cost < best_cost_and_pred[arc.nextstate].first) {
best_cost_and_pred[arc.nextstate].first = next_cost;
best_cost_and_pred[arc.nextstate].second = s;
}
}
double final_cost = ConvertToCost(clat.Final(s)),
tot_final = my_cost + final_cost;
if (tot_final < best_cost_and_pred[superfinal].first) {
best_cost_and_pred[superfinal].first = tot_final;
best_cost_and_pred[superfinal].second = s;
}
}
std::vector<StateId> states; // states on best path.
StateId cur_state = superfinal;
while (cur_state != 0) {
StateId prev_state = best_cost_and_pred[cur_state].second;
if (prev_state == kNoStateId) {
KALDI_WARN << "Failure in best-path algorithm for lattice (infinite costs?)";
return; // return empty best-path.
}
states.push_back(prev_state);
KALDI_ASSERT(cur_state != prev_state && "Lattice with cycles");
cur_state = prev_state;
}
std::reverse(states.begin(), states.end());
for (size_t i = 0; i < states.size(); i++)
shortest_path->AddState();
for (StateId s = 0; static_cast<size_t>(s) < states.size(); s++) {
if (s == 0) shortest_path->SetStart(s);
if (static_cast<size_t>(s + 1) < states.size()) { // transition to next state.
bool have_arc = false;
Arc cur_arc;
for (ArcIterator<CompactLattice> aiter(clat, states[s]);
!aiter.Done();
aiter.Next()) {
const Arc &arc = aiter.Value();
if (arc.nextstate == states[s+1]) {
if (!have_arc ||
ConvertToCost(arc.weight) < ConvertToCost(cur_arc.weight)) {
cur_arc = arc;
have_arc = true;
}
}
}
KALDI_ASSERT(have_arc && "Code error.");
shortest_path->AddArc(s, Arc(cur_arc.ilabel, cur_arc.olabel,
cur_arc.weight, s+1));
} else { // final-prob.
shortest_path->SetFinal(s, clat.Final(states[s]));
}
}
}
void AddWordInsPenToCompactLattice(BaseFloat word_ins_penalty,
CompactLattice *clat) {
typedef CompactLatticeArc Arc;
int32 num_states = clat->NumStates();
//scan the lattice
for (int32 state = 0; state < num_states; state++) {
for (fst::MutableArcIterator<CompactLattice> aiter(clat, state);
!aiter.Done(); aiter.Next()) {
Arc arc(aiter.Value());
if (arc.ilabel != 0) { // if there is a word on this arc
LatticeWeight weight = arc.weight.Weight();
// add word insertion penalty to lattice
weight.SetValue1( weight.Value1() + word_ins_penalty);
arc.weight.SetWeight(weight);
aiter.SetValue(arc);
}
} // end looping over arcs
} // end looping over states
}
struct ClatRescoreTuple {
ClatRescoreTuple(int32 state, int32 arc, int32 tid):
state_id(state), arc_id(arc), tid(tid) { }
int32 state_id;
int32 arc_id;
int32 tid;
};
/** RescoreCompactLatticeInternal is the internal code for both
RescoreCompactLattice and RescoreCompatLatticeSpeedup. For
RescoreCompactLattice, "tmodel" will be NULL and speedup_factor will be 1.0.
*/
bool RescoreCompactLatticeInternal(
const TransitionModel *tmodel,
BaseFloat speedup_factor,
DecodableInterface *decodable,
CompactLattice *clat) {
KALDI_ASSERT(speedup_factor >= 1.0);
if (clat->NumStates() == 0) {
KALDI_WARN << "Rescoring empty lattice";
return false;
}
if (!clat->Properties(fst::kTopSorted, true)) {
if (fst::TopSort(clat) == false) {
KALDI_WARN << "Cycles detected in lattice.";
return false;
}
}
std::vector<int32> state_times;
int32 utt_len = kaldi::CompactLatticeStateTimes(*clat, &state_times);
std::vector<std::vector<ClatRescoreTuple> > time_to_state(utt_len);
int32 num_states = clat->NumStates();
KALDI_ASSERT(num_states == state_times.size());
for (size_t state = 0; state < num_states; state++) {
KALDI_ASSERT(state_times[state] >= 0);
int32 t = state_times[state];
int32 arc_id = 0;
for (fst::MutableArcIterator<CompactLattice> aiter(clat, state);
!aiter.Done(); aiter.Next(), arc_id++) {
CompactLatticeArc arc = aiter.Value();
std::vector<int32> arc_string = arc.weight.String();
for (size_t offset = 0; offset < arc_string.size(); offset++) {
if (t < utt_len) { // end state may be past this..
int32 tid = arc_string[offset];
time_to_state[t+offset].push_back(ClatRescoreTuple(state, arc_id, tid));
} else {
if (t != utt_len) {
KALDI_WARN << "There appears to be lattice/feature mismatch, "
<< "aborting.";
return false;
}
}
}
}
if (clat->Final(state) != CompactLatticeWeight::Zero()) {
arc_id = -1;
std::vector<int32> arc_string = clat->Final(state).String();
for (size_t offset = 0; offset < arc_string.size(); offset++) {
KALDI_ASSERT(t + offset < utt_len); // already checked in
// CompactLatticeStateTimes, so would be code error.
time_to_state[t+offset].push_back(
ClatRescoreTuple(state, arc_id, arc_string[offset]));
}
}
}
for (int32 t = 0; t < utt_len; t++) {
if ((t < utt_len - 1) && decodable->IsLastFrame(t)) {
KALDI_WARN << "Features are too short for lattice: utt-len is "
<< utt_len << ", " << t << " is last frame";
return false;
}
// frame_scale is the scale we put on the computed acoustic probs for this
// frame. It will always be 1.0 if tmodel == NULL (i.e. if we are not doing
// the "speedup" code). For frames with multiple pdf-ids it will be one.
// For frames with only one pdf-id, it will equal speedup_factor (>=1.0)
// with probability 1.0 / speedup_factor, and zero otherwise. If it is zero,
// we can avoid computing the probabilities.
BaseFloat frame_scale = 1.0;
KALDI_ASSERT(!time_to_state[t].empty());
if (tmodel != NULL) {
int32 pdf_id = tmodel->TransitionIdToPdf(time_to_state[t][0].tid);
bool frame_has_multiple_pdfs = false;
for (size_t i = 1; i < time_to_state[t].size(); i++) {
if (tmodel->TransitionIdToPdf(time_to_state[t][i].tid) != pdf_id) {
frame_has_multiple_pdfs = true;
break;
}
}
if (frame_has_multiple_pdfs) {
frame_scale = 1.0;
} else {
if (WithProb(1.0 / speedup_factor)) {
frame_scale = speedup_factor;
} else {
frame_scale = 0.0;
}
}
if (frame_scale == 0.0)
continue; // the code below would be pointless.
}
for (size_t i = 0; i < time_to_state[t].size(); i++) {
int32 state = time_to_state[t][i].state_id;
int32 arc_id = time_to_state[t][i].arc_id;
int32 tid = time_to_state[t][i].tid;
if (arc_id == -1) { // Final state
// Access the trans_id
CompactLatticeWeight curr_clat_weight = clat->Final(state);
// Calculate likelihood
BaseFloat log_like = decodable->LogLikelihood(t, tid) * frame_scale;
// update weight
CompactLatticeWeight new_clat_weight = curr_clat_weight;
LatticeWeight new_lat_weight = new_clat_weight.Weight();
new_lat_weight.SetValue2(-log_like + curr_clat_weight.Weight().Value2());
new_clat_weight.SetWeight(new_lat_weight);
clat->SetFinal(state, new_clat_weight);
} else {
fst::MutableArcIterator<CompactLattice> aiter(clat, state);
aiter.Seek(arc_id);
CompactLatticeArc arc = aiter.Value();
// Calculate likelihood
BaseFloat log_like = decodable->LogLikelihood(t, tid) * frame_scale;
// update weight
LatticeWeight new_weight = arc.weight.Weight();
new_weight.SetValue2(-log_like + arc.weight.Weight().Value2());
arc.weight.SetWeight(new_weight);
aiter.SetValue(arc);
}
}
}
return true;
}
bool RescoreCompactLatticeSpeedup(
const TransitionModel &tmodel,
BaseFloat speedup_factor,
DecodableInterface *decodable,
CompactLattice *clat) {
return RescoreCompactLatticeInternal(&tmodel, speedup_factor, decodable, clat);
}
bool RescoreCompactLattice(DecodableInterface *decodable,
CompactLattice *clat) {
return RescoreCompactLatticeInternal(NULL, 1.0, decodable, clat);
}
bool RescoreLattice(DecodableInterface *decodable,
Lattice *lat) {
if (lat->NumStates() == 0) {
KALDI_WARN << "Rescoring empty lattice";
return false;
}
if (!lat->Properties(fst::kTopSorted, true)) {
if (fst::TopSort(lat) == false) {
KALDI_WARN << "Cycles detected in lattice.";
return false;
}
}
std::vector<int32> state_times;
int32 utt_len = kaldi::LatticeStateTimes(*lat, &state_times);
std::vector<std::vector<int32> > time_to_state(utt_len );
int32 num_states = lat->NumStates();
KALDI_ASSERT(num_states == state_times.size());
for (size_t state = 0; state < num_states; state++) {
int32 t = state_times[state];
// Don't check t >= 0 because non-accessible states could have t = -1.
KALDI_ASSERT(t <= utt_len);
if (t >= 0 && t < utt_len)
time_to_state[t].push_back(state);
}
for (int32 t = 0; t < utt_len; t++) {
if ((t < utt_len - 1) && decodable->IsLastFrame(t)) {
KALDI_WARN << "Features are too short for lattice: utt-len is "
<< utt_len << ", " << t << " is last frame";
return false;
}
for (size_t i = 0; i < time_to_state[t].size(); i++) {
int32 state = time_to_state[t][i];
for (fst::MutableArcIterator<Lattice> aiter(lat, state);
!aiter.Done(); aiter.Next()) {
LatticeArc arc = aiter.Value();
if (arc.ilabel != 0) {
int32 trans_id = arc.ilabel; // Note: it doesn't necessarily
// have to be a transition-id, just whatever the Decodable
// object is expecting, but it's normally a transition-id.
BaseFloat log_like = decodable->LogLikelihood(t, trans_id);
arc.weight.SetValue2(-log_like + arc.weight.Value2());
aiter.SetValue(arc);
}
}
}
}
return true;
}
BaseFloat LatticeForwardBackwardMmi(
const TransitionModel &tmodel,
const Lattice &lat,
const std::vector<int32> &num_ali,
bool drop_frames,
bool convert_to_pdf_ids,
bool cancel,
Posterior *post) {
// First compute the MMI posteriors.
Posterior den_post;
BaseFloat ans = LatticeForwardBackward(lat,
&den_post,
NULL);
Posterior num_post;
AlignmentToPosterior(num_ali, &num_post);
// Now negate the MMI posteriors and add the numerator
// posteriors.
ScalePosterior(-1.0, &den_post);
if (convert_to_pdf_ids) {
Posterior num_tmp;
ConvertPosteriorToPdfs(tmodel, num_post, &num_tmp);
num_tmp.swap(num_post);
Posterior den_tmp;
ConvertPosteriorToPdfs(tmodel, den_post, &den_tmp);
den_tmp.swap(den_post);
}
MergePosteriors(num_post, den_post,
cancel, drop_frames, post);
return ans;
}
int32 LongestSentenceLength(const Lattice &lat) {
typedef Lattice::Arc Arc;
typedef Arc::Label Label;
typedef Arc::StateId StateId;
if (lat.Properties(fst::kTopSorted, true) == 0) {
Lattice lat_copy(lat);
if (!TopSort(&lat_copy))
KALDI_ERR << "Was not able to topologically sort lattice (cycles found?)";
return LongestSentenceLength(lat_copy);
}
std::vector<int32> max_length(lat.NumStates(), 0);
int32 lattice_max_length = 0;
for (StateId s = 0; s < lat.NumStates(); s++) {
int32 this_max_length = max_length[s];
for (fst::ArcIterator<Lattice> aiter(lat, s); !aiter.Done(); aiter.Next()) {
const Arc &arc = aiter.Value();
bool arc_has_word = (arc.olabel != 0);
StateId nextstate = arc.nextstate;
KALDI_ASSERT(static_cast<size_t>(nextstate) < max_length.size());
if (arc_has_word) {
// A lattice should ideally not have cycles anyway; a cycle with a word
// on is something very bad.
KALDI_ASSERT(nextstate > s && "Lattice has cycles with words on.");
max_length[nextstate] = std::max(max_length[nextstate],
this_max_length + 1);
} else {
max_length[nextstate] = std::max(max_length[nextstate],
this_max_length);
}
}
if (lat.Final(s) != LatticeWeight::Zero())
lattice_max_length = std::max(lattice_max_length, max_length[s]);
}
return lattice_max_length;
}
int32 LongestSentenceLength(const CompactLattice &clat) {
typedef CompactLattice::Arc Arc;
typedef Arc::Label Label;
typedef Arc::StateId StateId;
if (clat.Properties(fst::kTopSorted, true) == 0) {
CompactLattice clat_copy(clat);
if (!TopSort(&clat_copy))
KALDI_ERR << "Was not able to topologically sort lattice (cycles found?)";
return LongestSentenceLength(clat_copy);
}
std::vector<int32> max_length(clat.NumStates(), 0);
int32 lattice_max_length = 0;
for (StateId s = 0; s < clat.NumStates(); s++) {
int32 this_max_length = max_length[s];
for (fst::ArcIterator<CompactLattice> aiter(clat, s);
!aiter.Done(); aiter.Next()) {
const Arc &arc = aiter.Value();
bool arc_has_word = (arc.ilabel != 0); // note: olabel == ilabel.
// also note: for normal CompactLattice, e.g. as produced by
// determinization, all arcs will have nonzero labels, but the user might
// decide to remplace some of the labels with zero for some reason, and we
// want to support this.
StateId nextstate = arc.nextstate;
KALDI_ASSERT(static_cast<size_t>(nextstate) < max_length.size());
KALDI_ASSERT(nextstate > s && "CompactLattice has cycles");
if (arc_has_word)
max_length[nextstate] = std::max(max_length[nextstate],
this_max_length + 1);
else
max_length[nextstate] = std::max(max_length[nextstate],
this_max_length);
}
if (clat.Final(s) != CompactLatticeWeight::Zero())
lattice_max_length = std::max(lattice_max_length, max_length[s]);
}
return lattice_max_length;
}
void ComposeCompactLatticeDeterministic(
const CompactLattice& clat,
fst::DeterministicOnDemandFst<fst::StdArc>* det_fst,
CompactLattice* composed_clat) {
// StdFst::Arc and CompactLatticeArc has the same StateId type.
typedef fst::StdArc::StateId StateId;
typedef fst::StdArc::Weight Weight1;
typedef CompactLatticeArc::Weight Weight2;
typedef std::pair<StateId, StateId> StatePair;
typedef unordered_map<StatePair, StateId, PairHasher<StateId> > MapType;
typedef MapType::iterator IterType;
// Empties the output FST.
KALDI_ASSERT(composed_clat != NULL);
composed_clat->DeleteStates();
MapType state_map;
std::queue<StatePair> state_queue;
// Sets start state in <composed_clat>.
StateId start_state = composed_clat->AddState();
StatePair start_pair(clat.Start(), det_fst->Start());
composed_clat->SetStart(start_state);
state_queue.push(start_pair);
std::pair<IterType, bool> result =
state_map.insert(std::make_pair(start_pair, start_state));
KALDI_ASSERT(result.second == true);
// Starts composition here.
while (!state_queue.empty()) {
// Gets the first state in the queue.
StatePair s = state_queue.front();
StateId s1 = s.first;
StateId s2 = s.second;
state_queue.pop();
Weight2 clat_final = clat.Final(s1);
if (clat_final.Weight().Value1() !=
std::numeric_limits<BaseFloat>::infinity()) {
// Test for whether the final-prob of state s1 was zero.
Weight1 det_fst_final = det_fst->Final(s2);
if (det_fst_final.Value() !=
std::numeric_limits<BaseFloat>::infinity()) {
// Test for whether the final-prob of state s2 was zero. If neither
// source-state final prob was zero, then we should create final state
// in fst_composed. We compute the product manually since this is more
// efficient.
Weight2 final_weight(LatticeWeight(clat_final.Weight().Value1() +
det_fst_final.Value(),
clat_final.Weight().Value2()),
clat_final.String());
// we can assume final_weight is not Zero(), since neither of
// the sources was zero.
KALDI_ASSERT(state_map.find(s) != state_map.end());
composed_clat->SetFinal(state_map[s], final_weight);
}
}
// Loops over pair of edges at s1 and s2.
for (fst::ArcIterator<CompactLattice> aiter(clat, s1);
!aiter.Done(); aiter.Next()) {
const CompactLatticeArc& arc1 = aiter.Value();
fst::StdArc arc2;
StateId next_state1 = arc1.nextstate, next_state2;
bool matched = false;
if (arc1.olabel == 0) {
// If the symbol on <arc1> is <epsilon>, we transit to the next state
// for <clat>, but keep <det_fst> at the current state.
matched = true;
next_state2 = s2;
} else {
// Otherwise try to find the matched arc in <det_fst>.
matched = det_fst->GetArc(s2, arc1.olabel, &arc2);
if (matched) {
next_state2 = arc2.nextstate;
}
}
// If matched arc is found in <det_fst>, then we have to add new arcs to
// <composed_clat>.
if (matched) {
StatePair next_state_pair(next_state1, next_state2);
IterType siter = state_map.find(next_state_pair);
StateId next_state;
// Adds composed state to <state_map>.
if (siter == state_map.end()) {
// If the composed state has not been created yet, create it.
next_state = composed_clat->AddState();
std::pair<const StatePair, StateId> next_state_map(next_state_pair,
next_state);
std::pair<IterType, bool> result = state_map.insert(next_state_map);
KALDI_ASSERT(result.second);
state_queue.push(next_state_pair);
} else {
// If the composed state is already in <state_map>, we can directly
// use that.
next_state = siter->second;
}
// Adds arc to <composed_clat>.
if (arc1.olabel == 0) {
composed_clat->AddArc(state_map[s],
CompactLatticeArc(arc1.ilabel, 0,
arc1.weight, next_state));
} else {
Weight2 composed_weight(
LatticeWeight(arc1.weight.Weight().Value1() +
arc2.weight.Value(),
arc1.weight.Weight().Value2()),
arc1.weight.String());
composed_clat->AddArc(state_map[s],
CompactLatticeArc(arc1.ilabel, arc2.olabel,
composed_weight, next_state));
}
}
}
}
fst::Connect(composed_clat);
}
void ComputeAcousticScoresMap(
const Lattice &lat,
unordered_map<std::pair<int32, int32>, std::pair<BaseFloat, int32>,
PairHasher<int32> > *acoustic_scores) {
// typedef the arc, weight types
typedef Lattice::Arc Arc;
typedef Arc::Weight LatticeWeight;
typedef Arc::StateId StateId;
acoustic_scores->clear();
std::vector<int32> state_times;
LatticeStateTimes(lat, &state_times); // Assumes the input is top sorted
KALDI_ASSERT(lat.Start() == 0);
for (StateId s = 0; s < lat.NumStates(); s++) {
int32 t = state_times[s];
for (fst::ArcIterator<Lattice> aiter(lat, s); !aiter.Done();
aiter.Next()) {
const Arc &arc = aiter.Value();
const LatticeWeight &weight = arc.weight;
int32 tid = arc.ilabel;
if (tid != 0) {
unordered_map<std::pair<int32, int32>, std::pair<BaseFloat, int32>,
PairHasher<int32> >::iterator it = acoustic_scores->find(std::make_pair(t, tid));
if (it == acoustic_scores->end()) {
acoustic_scores->insert(std::make_pair(std::make_pair(t, tid),
std::make_pair(weight.Value2(), 1)));
} else {
if (it->second.second == 2
&& it->second.first / it->second.second != weight.Value2()) {
KALDI_VLOG(2) << "Transitions on the same frame have different "
<< "acoustic costs for tid " << tid << "; "
<< it->second.first / it->second.second
<< " vs " << weight.Value2();
}
it->second.first += weight.Value2();
it->second.second++;
}
} else {
// Arcs with epsilon input label (tid) must have 0 acoustic cost
KALDI_ASSERT(weight.Value2() == 0);
}
}
LatticeWeight f = lat.Final(s);
if (f != LatticeWeight::Zero()) {
// Final acoustic cost must be 0 as we are reading from
// non-determinized, non-compact lattice
KALDI_ASSERT(f.Value2() == 0.0);
}
}
}
void ReplaceAcousticScoresFromMap(
const unordered_map<std::pair<int32, int32>, std::pair<BaseFloat, int32>,
PairHasher<int32> > &acoustic_scores,
Lattice *lat) {
// typedef the arc, weight types
typedef Lattice::Arc Arc;
typedef Arc::Weight LatticeWeight;
typedef Arc::StateId StateId;
TopSortLatticeIfNeeded(lat);
std::vector<int32> state_times;
LatticeStateTimes(*lat, &state_times);
KALDI_ASSERT(lat->Start() == 0);
for (StateId s = 0; s < lat->NumStates(); s++) {
int32 t = state_times[s];
for (fst::MutableArcIterator<Lattice> aiter(lat, s);
!aiter.Done(); aiter.Next()) {
Arc arc(aiter.Value());
int32 tid = arc.ilabel;
if (tid != 0) {
unordered_map<std::pair<int32, int32>, std::pair<BaseFloat, int32>,
PairHasher<int32> >::const_iterator it = acoustic_scores.find(std::make_pair(t, tid));
if (it == acoustic_scores.end()) {
KALDI_ERR << "Could not find tid " << tid << " at time " << t
<< " in the acoustic scores map.";
} else {
arc.weight.SetValue2(it->second.first / it->second.second);
}
} else {
// For epsilon arcs, set acoustic cost to 0.0
arc.weight.SetValue2(0.0);
}
aiter.SetValue(arc);
}
LatticeWeight f = lat->Final(s);
if (f != LatticeWeight::Zero()) {
// Set final acoustic cost to 0.0
f.SetValue2(0.0);
lat->SetFinal(s, f);
}
}
}
} // namespace kaldi
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