online-server-gmm-decode-faster.cc
8.06 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
// onlinebin/online-server-gmm-decode-faster.cc
// Copyright 2012 Cisco Systems (author: Matthias Paulik)
// 2012 Vassil Panayotov
// 2013 Johns Hopkins University (author: Daniel Povey)
// 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 "feat/feature-mfcc.h"
#include "online/online-feat-input.h"
#include "online/online-decodable.h"
#include "online/online-faster-decoder.h"
#include "online/onlinebin-util.h"
namespace kaldi {
void SendPartialResult(const std::vector<int32>& words,
const fst::SymbolTable *word_syms,
const bool line_break,
const int32 serv_sock,
const sockaddr_in &client_addr) {
KALDI_ASSERT(word_syms != NULL);
std::stringstream sstream;
for (size_t i = 0; i < words.size(); i++) {
std::string word = word_syms->Find(words[i]);
if (word == "")
KALDI_ERR << "Word-id " << words[i] <<" not in symbol table.";
sstream << word << ' ';
}
if (line_break)
sstream << "\n\n";
ssize_t sent = sendto(serv_sock, sstream.str().c_str(), sstream.str().size(),
0, reinterpret_cast<const sockaddr*>(&client_addr),
sizeof(client_addr));
if (sent == -1)
KALDI_WARN << "sendto() call failed when tried to send recognition results";
}
} // namespace kaldi
int main(int argc, char *argv[]) {
try {
using namespace kaldi;
using namespace fst;
typedef kaldi::int32 int32;
// Up to delta-delta derivative features are calculated (unless LDA is used)
const int32 kDeltaOrder = 2;
const char *usage =
"Decode speech, using feature batches received over a network connection\n\n"
"Utterance segmentation is done on-the-fly.\n"
"Feature splicing/LDA transform is used, if the optional(last) argument "
"is given.\n"
"Otherwise delta/delta-delta(2-nd order) features are produced.\n\n"
"Usage: online-server-gmm-decode-faster [options] model-in"
"fst-in word-symbol-table silence-phones udp-port [lda-matrix-in]\n\n"
"Example: online-server-gmm-decode-faster --rt-min=0.3 --rt-max=0.5 "
"--max-active=4000 --beam=12.0 --acoustic-scale=0.0769 "
"model HCLG.fst words.txt '1:2:3:4:5' 1234 lda-matrix";
ParseOptions po(usage);
BaseFloat acoustic_scale = 0.1;
int32 cmn_window = 600,
min_cmn_window = 100; // adds 1 second latency, only at utterance start.
int32 right_context = 4, left_context = 4;
kaldi::DeltaFeaturesOptions delta_opts;
delta_opts.Register(&po);
OnlineFasterDecoderOpts decoder_opts;
OnlineFeatureMatrixOptions feature_reading_opts;
decoder_opts.Register(&po, true);
feature_reading_opts.Register(&po);
po.Register("left-context", &left_context, "Number of frames of left context");
po.Register("right-context", &right_context, "Number of frames of right context");
po.Register("acoustic-scale", &acoustic_scale,
"Scaling factor for acoustic likelihoods");
po.Register("cmn-window", &cmn_window,
"Number of feat. vectors used in the running average CMN calculation");
po.Register("min-cmn-window", &min_cmn_window,
"Minumum CMN window used at start of decoding (adds "
"latency only at start)");
po.Read(argc, argv);
if (po.NumArgs() != 5 && po.NumArgs() != 6) {
po.PrintUsage();
return 1;
}
std::string model_rxfilename = po.GetArg(1),
fst_rxfilename = po.GetArg(2),
word_syms_filename = po.GetArg(3),
silence_phones_str = po.GetArg(4),
lda_mat_rspecifier = po.GetOptArg(6);
int32 udp_port = atoi(po.GetArg(5).c_str());
Matrix<BaseFloat> lda_transform;
if (lda_mat_rspecifier != "") {
bool binary_in;
Input ki(lda_mat_rspecifier, &binary_in);
lda_transform.Read(ki.Stream(), binary_in);
}
std::vector<int32> silence_phones;
if (!SplitStringToIntegers(silence_phones_str, ":", false, &silence_phones))
KALDI_ERR << "Invalid silence-phones string " << silence_phones_str;
if (silence_phones.empty())
KALDI_ERR << "No silence phones given!";
TransitionModel trans_model;
AmDiagGmm am_gmm;
{
bool binary;
Input ki(model_rxfilename, &binary);
trans_model.Read(ki.Stream(), binary);
am_gmm.Read(ki.Stream(), binary);
}
fst::SymbolTable *word_syms = NULL;
if (!(word_syms = fst::SymbolTable::ReadText(word_syms_filename)))
KALDI_ERR << "Could not read symbol table from file "
<< word_syms_filename;
fst::Fst<fst::StdArc> *decode_fst = ReadDecodeGraph(fst_rxfilename);
// We are not properly registering/exposing MFCC and frame extraction options,
// because there are parts of the online decoding code, where some of these
// options are hardwired(ToDo: we should fix this at some point)
MfccOptions mfcc_opts;
mfcc_opts.use_energy = false;
OnlineFasterDecoder decoder(*decode_fst, decoder_opts,
silence_phones, trans_model);
VectorFst<LatticeArc> out_fst;
int32 feature_dim = mfcc_opts.num_ceps; // default to 13 right now.
OnlineUdpInput udp_input(udp_port, feature_dim);
OnlineCmnInput cmn_input(&udp_input, cmn_window, min_cmn_window);
OnlineFeatInputItf *feat_transform = 0;
if (lda_mat_rspecifier != "") {
feat_transform = new OnlineLdaInput(
&cmn_input, lda_transform,
left_context, right_context);
} else {
DeltaFeaturesOptions opts;
opts.order = kDeltaOrder;
feat_transform = new OnlineDeltaInput(opts, &cmn_input);
}
// feature_reading_opts contains number of retries, batch size.
OnlineFeatureMatrix feature_matrix(feature_reading_opts,
feat_transform);
OnlineDecodableDiagGmmScaled decodable(am_gmm, trans_model, acoustic_scale,
&feature_matrix);
std::cerr << std::endl << "Listening on UDP port "
<< udp_port << " ... " << std::endl;
bool partial_res = false;
while (1) {
OnlineFasterDecoder::DecodeState dstate = decoder.Decode(&decodable);
std::vector<int32> word_ids;
if (dstate & (decoder.kEndFeats | decoder.kEndUtt)) {
decoder.FinishTraceBack(&out_fst);
fst::GetLinearSymbolSequence(out_fst,
static_cast<vector<int32> *>(0),
&word_ids,
static_cast<LatticeArc::Weight*>(0));
SendPartialResult(word_ids, word_syms, partial_res || word_ids.size(),
udp_input.descriptor(), udp_input.client_addr());
partial_res = false;
} else {
if (decoder.PartialTraceback(&out_fst)) {
fst::GetLinearSymbolSequence(out_fst,
static_cast<vector<int32> *>(0),
&word_ids,
static_cast<LatticeArc::Weight*>(0));
SendPartialResult(word_ids, word_syms, false,
udp_input.descriptor(), udp_input.client_addr());
if (!partial_res)
partial_res = (word_ids.size() > 0);
}
}
}
delete feat_transform;
delete word_syms;
delete decode_fst;
return 0;
} catch(const std::exception& e) {
std::cerr << e.what();
return -1;
}
} // main()