forked from rampa069/PhnRec
/
srec.cpp
1635 lines (1422 loc) · 46.8 KB
/
srec.cpp
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/**************************************************************************
* copyright : (C) 2004-2006 by Petr Schwarz & Pavel Matejka *
* UPGM,FIT,VUT,Brno *
* email : {schwarzp,matejkap}@fit.vutbr.cz *
**************************************************************************
* *
* This program is free software; you can redistribute it and/or modify *
* it under the terms of the GNU General Public License as published by *
* the Free Software Foundation; either version 2 of the License, or *
* (at your option) any later version. *
* *
**************************************************************************/
#include <stdio.h>
#include <stdlib.h>
#include <assert.h>
#include "dspc.h"
#include "srec.h"
#include "alaw.h"
#include "filename.h"
#ifdef __CYGWIN__
#include <sys/stat.h>
#endif
#ifdef WIN32
extern const char *dirSep = "\\";
#else
extern const char *dirSep = "/";
#endif
// variable table - these variables can be set in a configuration file
config_variable cfg_entry[] =
{
{"source", "format", CE_STRING, "lin16"},
{"source", "sample_freq", CE_INT, "8000"},
{"source", "scale", CE_FLOAT, "1.0f"},
{"source", "dc_shift", CE_FLOAT, "0.0f"},
{"source", "noise_level", CE_FLOAT, "0.0f"},
{"params", "kind", CE_STRING, "fbanks"},
{"params", "suffix", CE_STRING, "mel"},
{"melbanks", "nbanks", CE_INT, "15"},
{"melbanks", "nbanks_full", CE_INT, "-1"},
{"melbanks", "lower_freq", CE_FLOAT, "0"},
{"melbanks", "higher_freq", CE_FLOAT, "4000"},
{"melbanks", "vector_size", CE_INT, "200"},
{"melbanks", "vector_step", CE_INT, "80"},
{"melbanks", "preem_coef", CE_FLOAT, "0.0"},
{"melbanks", "z_mean_source", CE_BOOL, "false"},
{"plp", "order", CE_INT, "12"},
{"plp", "compress_fact", CE_FLOAT, "0.3333333"},
{"plp", "cep_lifter", CE_FLOAT, "22"},
{"plp", "cep_scale", CE_FLOAT, "10"},
{"plp", "add_c0", CE_BOOL, "false"},
{"onlinenorm", "estim_interval", CE_INT, "0"},
{"onlinenorm", "signal_est_end", CE_BOOL, "false"},
{"onlinenorm", "file", CE_STRING, "none"},
{"onlinenorm", "mean_norm", CE_BOOL, "false"},
{"onlinenorm", "var_norm", CE_BOOL, "false"},
{"onlinenorm", "scale_to_gvar", CE_BOOL, "false"},
{"offlinenorm", "sent_mean_norm", CE_BOOL, "false"},
{"offlinenorm", "sent_var_norm", CE_BOOL, "false"},
{"offlinenorm", "sent_std_thr", CE_FLOAT, "0.01"},
{"offlinenorm", "sent_max_norm", CE_BOOL, "false"},
{"offlinenorm", "sent_chmax_norm", CE_BOOL, "false"},
{"framenorm", "min_floor", CE_FLOAT, "-9999.9"},
{"framenorm", "shift", CE_FLOAT, "0"},
{"posteriors", "system", CE_STRING, "1BT_DCT"},
{"posteriors", "length", CE_INT, "31"},
{"posteriors", "add_c0", CE_BOOL, "true"},
{"posteriors", "hamming", CE_BOOL, "false"},
{"posteriors", "suffix", CE_STRING, "lop"},
{"posteriors", "bunch_size", CE_STRING, "1"},
{"posteriors", "enabled", CE_BOOL, "true"},
{"posteriors", "softening_func", CE_STRING, "none 0 0 0"},
{"decoder", "type", CE_STRING, "stkint"},
{"decoder", "wpenalty", CE_FLOAT, "-2.0"},
{"decoder", "lm_scale", CE_FLOAT, "1.0"},
{"decoder", "time_pruning", CE_INT, "40"},
{"decoder", "mode", CE_STRING, "decode"},
{"decoder", "softening_func", CE_STRING, "log 0 0 0"},
{"decoder", "num_states_per_phn",CE_INT, "1"},
{"dirs", "tmp", CE_STRING, "$C/tmp"},
{"models", "hmm_defs", CE_STRING, "$T/models"},
{"models", "nstates", CE_INT, "3"},
{"models", "gen_from_phn_list", CE_BOOL, "false"},
{"dicts", "phoneme_list", CE_STRING, ""},
{"dicts", "lexicon1", CE_STRING, ""},
{"dicts", "lexicon2", CE_STRING, ""},
{"dicts", "lexicon1_save_bin", CE_BOOL, "false"},
{"dicts", "lexicon2_save_bin", CE_BOOL, "false"},
{"dicts", "keyword_list", CE_STRING, "none"},
{"dicts", "charset", CE_STRING, "eastevrope"},
{"networks", "default", CE_STRING, "$C/nets/network"},
{"networks", "gen_phn_loop", CE_BOOL, "false"},
{"networks", "gen_kws_net", CE_BOOL, "false"},
{"networks", "omit_phn", CE_STRING, "oth"},
{"labels", "suffix", CE_STRING, "rec"},
{"labels", "remove_path", CE_BOOL, "true"},
{"kws", "default_thr", CE_FLOAT, "-10.0"},
{"kws", "thresholds_file", CE_STRING, "none"},
{"gptransc", "rules", CE_STRING, "none"},
{"gptransc", "symbols", CE_STRING, "none"},
{"gptransc", "max_variants", CE_INT, "-1"},
{"gptransc", "scale_prob", CE_BOOL, "false"},
{"gptransc", "prob_thr", CE_FLOAT, "-1.0"},
{"phntransc", "mode", CE_STRING, "lexgpt"},
{0 , 0, 0, 0}
};
// source-format: lin8, lin16, alaw
// system-type: 3BT, 1BT, 1BT_DCT, LCRC
// decoder-mode: decode, kws
//-----------------------------------------------------------------------------------
// default error handler
void SpeechRec::MError(char *msg, void *arg)
{
fprintf(stderr, "ERROR: %s", msg);
exit(1);
}
// default logging handler
void SpeechRec::MLog(char *msg, void *arg)
{
fprintf(stdout, "%s", msg);
}
// default handler for the decoder output
void SpeechRec::OnWord(unsigned int message, char *word, long_long start, long_long stop, float score, void *tmp)
{
OnWordMLF(message, word, start, stop, score, (void *)stdout);
}
// handler used to dump labels to MLF
void SpeechRec::OnWordMLF(unsigned int message, char *word, long_long start, long_long stop, float score, void *tmp)
{
start /= 100000;
stop /= 100000;
if(start == 0)
{
fprintf((FILE *)tmp, "0");
}
else
{
fprintf((FILE *)tmp, "%u00000", (unsigned int)start);
}
if(stop == 0)
{
fprintf((FILE *)tmp, " 0");
}
else
{
fprintf((FILE *)tmp, " %u00000", (unsigned int)stop);
}
fprintf((FILE *)tmp, " %s %f\n", word, score);
}
//-----------------------------------------------------------------------------------
// softening function
float SpeechRec::SoftIgor(float v, float middPoint, float rightLog, float leftLog)
{
if(v < middPoint)
return logf(v * (1.0f / middPoint)) / logf(leftLog);
return -1.0f * logf(( 1.0f + ( -1.0f * v )) * (1.0f / (1.0f - middPoint))) / logf(rightLog);
}
float SpeechRec::SoftGMMBypass(float v, float middPoint, float rightLog, float leftLog)
{
return sqrtf(-2.0f * logf(v));
}
//-----------------------------------------------------------------------------------
SpeechRec::SpeechRec() :
errFunc(&MError),
logFunc(&MLog),
errArg(0),
logArg(0),
waveScale(1.0f),
waveDCShift(0.0f),
waveNoiseLevel(0.0f),
actualParams(&MB),
mTrapsEnabled(true),
waveform(0),
waveformLen(0),
params(0),
posteriors(0),
bunchSize(1),
bunchIdx(0),
lastParamVector(0),
postSoftFunc(&SoftNone),
postSoftArg1(0),
postSoftArg2(0),
postSoftArg3(0),
decSoftFunc(&SoftLog),
decSoftArg1(0),
decSoftArg2(0),
decSoftArg3(0),
DE(0)
{
}
SpeechRec::~SpeechRec()
{
if(params)
delete [] params;
if(posteriors)
delete [] posteriors;
if(DE)
delete DE;
}
void SpeechRec::SubstVars(char *dir_name, char *cfg_dir)
{
// replace dir separators /\ with the one used by system
CorrectDirSeparator(dir_name, dirSep);
if(strlen(dir_name) > 1 && (strncmp(dir_name, "$C", 2) == 0 || strncmp(dir_name, "$T", 2) == 0))
{
char buff[1024];
strcpy(buff, dir_name);
if(buff[1] == 'C')
sprintf(dir_name, "%s%s", cfg_dir, buff + 2);
else
sprintf(dir_name, "%s%s", C.GetString("dirs", "tmp"), buff + 2);
}
}
bool SpeechRec::Init(char *config_file)
{
// configuration
char config_dir[1024];
GetFilePath(config_file, config_dir);
C.SetVariableTable(cfg_entry);
C.SetCheckUnknownVariables(true);
int line;
int ret = C.Load(config_file, &line);
if(ret != EN_OK)
{
char msg[1024];
switch(ret)
{
case EN_UNKVAR:
sprintf(msg, "Unknown variable in configuration file '%s', line %d\n", config_file, line);
break;
case EN_BADVAL:
sprintf(msg, "Invalid argument for a vatiable in configuration file '%s', line %d\n", config_file, line);
break;
case EN_FILEERR:
sprintf(msg, "Can not open configuration file '%s'\n", config_file);
break;
case EN_INVVAR:
sprintf(msg, "Invalid notation of variable in configuration file '%s', line %d\n", config_file, line);
break;
}
MERROR(msg);
return false;
}
// substitute variables in directory and file names
// - temp dir
char tmpDir[1024];
char *pdir = C.GetString("dirs", "tmp");
strcpy(tmpDir, pdir);
SubstVars(tmpDir, config_dir);
C.SetString("dirs", "tmp", tmpDir);
#if defined WIN32 && !defined __CYGWIN__
mkdir(tmpDir);
#else
mkdir(tmpDir, 0xFFFF);
#endif
// - model file
char file[1024];
char *pfile;
pfile = C.GetString("models", "hmm_defs");
strcpy(file, pfile);
SubstVars(file, config_dir);
C.SetString("models", "hmm_defs", file);
// - phoneme list
pfile = C.GetString("dicts", "phoneme_list");
strcpy(file, pfile);
SubstVars(file, config_dir);
C.SetString("dicts", "phoneme_list", file);
// - network file
pfile = C.GetString("networks", "default");
strcpy(file, pfile);
SubstVars(file, config_dir);
C.SetString("networks", "default", file);
// - lexicon
pfile = C.GetString("dicts", "lexicon1");
strcpy(file, pfile);
SubstVars(file, config_dir);
C.SetString("dicts", "lexicon1", file);
//
pfile = C.GetString("dicts", "lexicon2");
strcpy(file, pfile);
SubstVars(file, config_dir);
C.SetString("dicts", "lexicon2", file);
// - keyword_list
pfile = C.GetString("dicts", "keyword_list");
strcpy(file, pfile);
SubstVars(file, config_dir);
C.SetString("dicts", "keyword_list", file);
// - thresholds file
pfile = C.GetString("kws", "thresholds_file");
strcpy(file, pfile);
SubstVars(file, config_dir);
C.SetString("kws", "thresholds_file", file);
// - grapheme to phoneme transcription rules
pfile = C.GetString("gptransc", "rules");
strcpy(file, pfile);
SubstVars(file, config_dir);
C.SetString("gptransc", "rules", file);
// - symbols for GP transcription rules
pfile = C.GetString("gptransc", "symbols");
strcpy(file, pfile);
SubstVars(file, config_dir);
C.SetString("gptransc", "symbols", file);
// - norm file
pfile = C.GetString("onlinenorm", "file");
strcpy(file, pfile);
SubstVars(file, config_dir);
C.SetString("onlinenorm", "file", file);
#ifndef PHNREC_ONLY
// automatic generation of hmm file
if(C.GetBool("models", "gen_from_phn_list"))
{
int err = PhnList2HMMDef(C.GetString("dicts", "phoneme_list"),
C.GetString("models", "hmm_defs"),
C.GetInt("models", "nstates"));
char msg[1024];
if(err != NGEN_OK)
{
switch(err)
{
case NGEN_INPUTFILE:
sprintf(msg, "Can not open the phoneme list: %s\n", C.GetString("dicts", "phoneme_list"));
break;
case NGEN_OUTPUTFILE:
sprintf(msg, "Can not create the HMM file: %s\n", C.GetString("models", "hmm_defs"));
break;
}
MERROR(msg);
return false;
}
}
// automatic generation of phoneme loop (word network)
if(C.GetBool("networks", "gen_phn_loop"))
{
char net_dir[1024];
GetFilePath(C.GetString("networks", "default"), net_dir);
#ifdef __WIN32
mkdir(net_dir);
#else
mkdir(net_dir, 0xFFFF);
#endif
int err = PhnList2PhnLoop(C.GetString("dicts", "phoneme_list"),
C.GetString("networks", "default"),
C.GetString("networks", "omit_phn"));
if(err != NGEN_OK)
{
char msg[1024];
switch(err)
{
case NGEN_INPUTFILE:
sprintf(msg, "Can not open the dictionary file: %s\n", C.GetString("dicts", "phoneme_list"));
break;
case NGEN_OUTPUTFILE:
sprintf(msg, "Can not create the network file: %s\n", C.GetString("networks", "default"));
break;
}
MERROR(msg);
return false;
}
}
// grapheme to phoneme transcription
if(strcmp(C.GetString("gptransc", "rules"), "none") != 0)
{
int ret = GPT.LoadRules(C.GetString("gptransc", "rules"));
if(ret != GPT_OK)
{
char msg[1024];
sprintf(msg, "Can not open grapheme to phoneme conversion rules: %s\n", C.GetString("gptransc", "rules"));
MERROR(msg);
return false;
}
if(strcmp(C.GetString("gptransc", "symbols"), "none") == 0)
{
char msg[1024];
sprintf(msg, "Symbols for grapheme to phoneme conversion rules have to be used (gptransc/symbols)\n");
MERROR(msg);
return false;
}
}
else
{
GPT.UnInitialize();
}
if(strcmp(C.GetString("gptransc", "symbols"), "none") != 0)
{
int ret = GPT.LoadSymbols(C.GetString("gptransc", "symbols"));
if(ret != GPT_OK)
{
char msg[1024];
sprintf(msg, "Can not open symbols for grapheme to phoneme conversion rules: %s\n", C.GetString("gptransc", "symbols"));
MERROR(msg);
return false;
}
}
GPT.SetMaxProns(C.GetInt("gptransc", "max_variants"));
GPT.SetScalePronProb(C.GetBool("gptransc", "scale_prob"));
GPT.SetLowestPronProb(C.GetFloat("gptransc", "prob_thr"));
// configure phoneme transcription (grapheme to phoneme transc and lexicon merger)
PT.SetLexicon(&Lex);
PT.SetGPTrans(&GPT);
KNG.SetPhnTrans(&PT);
// - load lexicons
Lex.Clear();
int i;
for(i = 1; i <= 2; i++)
{
char lexicon_tag[256];
sprintf(lexicon_tag, "lexicon%d", i);
char save_bin_tag[256];
sprintf(save_bin_tag, "lexicon%d_save_bin", i);
if(strcmp(C.GetString("dicts", lexicon_tag), "none") != 0)
{
char errWord[256];
int ret = Lex.Load(C.GetString("dicts", lexicon_tag), i - 1, C.GetBool("dicts", save_bin_tag), errWord);
if(ret != LEX_OK)
{
char msg[1024];
switch(ret)
{
case LEX_INPUTFILE:
sprintf(msg, "Can not open lexicon %s\n", C.GetString("dicts", lexicon_tag));
break;
case LEX_TRANSC:
sprintf(msg, "Invalid word transcription '%s', file %s\n", errWord, C.GetString("dicts", lexicon_tag));
break;
case LEX_ALREDYEXISTS:
sprintf(msg, "Word transctiption alredy exists '%s', file %s\n", errWord, C.GetString("dicts", lexicon_tag));
break;
case LEX_SYNTAX:
sprintf(msg, "Missing transcription for word '%s', file %s\n", errWord, C.GetString("dicts", lexicon_tag));
break;
}
MERROR(msg);
return false;
}
}
}
// kws network generator and phoneme transcription checker
// - load phoneme list
if(strcmp(C.GetString("dicts", "phoneme_list"), "none") != 0)
{
int ret1 = KNG.LoadPhnList(C.GetString("dicts", "phoneme_list"));
int ret2 = PTCheck.LoadPhnList(C.GetString("dicts", "phoneme_list"));
if(ret1 == KWSNGE_INPUTFILE || ret2 == PTCE_INPUTFILE)
{
char msg[1024];
sprintf(msg, "Can not open phoneme list %s\n", C.GetString("dicts", "phoneme_list"));
MERROR(msg);
return false;
}
}
if(C.GetBool("networks", "gen_kws_net"))
{
char unkWord[256];
ret = KNG.GenerateFromFile(C.GetString("dicts", "keyword_list"), C.GetString("networks", "default"), unkWord);
if(ret != KWSNGE_OK)
{
char msg[1024];
switch(ret)
{
case KWSNGE_INPUTFILE:
sprintf(msg, "Can not open keyword list %s\n", C.GetString("dicts", "keyword_list"));
break;
case KWSNGE_OUTPUTFILE:
sprintf(msg, "Can not create network file %s\n", C.GetString("networks", "default"));
break;
case KWSNGE_MISSINGWORD:
sprintf(msg, "Lexicon does not contain transcription for: %s\n", unkWord);
break;
case KWSNGE_NOTINIT:
sprintf(msg, "Keyword network generator is not fully initialized. It needs phoneme list and lexicon\n");
break;
}
MERROR(msg);
return false;
}
}
// load threshold file
THR.SetDefaultThr(C.GetFloat("kws", "default_thr"));
char *thr_file = C.GetString("kws", "thresholds_file");
if(strcmp(thr_file, "none") != 0)
{
bool ok = THR.LoadThresholds(thr_file);
if(!ok)
{
char msg[1024];
sprintf(msg, "Can not open thresholds file %s\n", thr_file);
MERROR(msg);
return false;
}
}
else
{
THR.Clear();
}
#endif // PHNREC_ONLY
// source
waveFormat = Str2WaveFormat(C.GetString("source", "format"));
waveScale = C.GetFloat("source", "scale");
waveDCShift = C.GetFloat("source", "dc_shift");
waveNoiseLevel = C.GetFloat("source", "noise_level");
MLOG("\nSystem initialization\n");
// param kind - melbanks, PLP
paramKind = Str2ParamKind(C.GetString("params", "kind"));
switch(paramKind)
{
case pkFBanks: // mel-banks
MLOG(" - mel-banks ...\n");
MB.SetBanksNum(C.GetInt("melbanks", "nbanks"));
MB.SetBanksFullNum(C.GetInt("melbanks", "nbanks_full"));
MB.SetSampleFreq(C.GetInt("source", "sample_freq"));
MB.SetVectorSize(C.GetInt("melbanks", "vector_size"));
MB.SetStep(C.GetInt("melbanks", "vector_step"));
MB.SetPreemCoef(C.GetFloat("melbanks", "preem_coef"));
MB.SetZMeanSource(C.GetBool("melbanks", "z_mean_source"));
MB.SetLowFreq(C.GetFloat("melbanks", "lower_freq"));
MB.SetHighFreq(C.GetFloat("melbanks", "higher_freq"));
actualParams = &MB;
break;
#ifndef PHNREC_ONLY
case pkPLP: // plp
MLOG(" - plp ...\n");
PLP.SetBanksNum(C.GetInt("melbanks", "nbanks"));
PLP.SetBanksFullNum(C.GetInt("melbanks", "nbanks_full"));
PLP.SetSampleFreq(C.GetInt("source", "sample_freq"));
PLP.SetVectorSize(C.GetInt("melbanks", "vector_size"));
PLP.SetStep(C.GetInt("melbanks", "vector_step"));
PLP.SetPreemCoef(C.GetFloat("melbanks", "preem_coef"));
PLP.SetZMeanSource(C.GetBool("melbanks", "z_mean_source"));
PLP.SetLowFreq(C.GetFloat("melbanks", "lower_freq"));
PLP.SetHighFreq(C.GetFloat("melbanks", "higher_freq"));
PLP.SetLPCOrder(C.GetInt("plp", "order"));
PLP.SetCompressFactor(C.GetFloat("plp", "compress_fact"));
PLP.SetCepstralLifter(C.GetFloat("plp", "cep_lifter"));
PLP.SetCepstralScale(C.GetFloat("plp", "cep_scale"));
PLP.SetAddC0(C.GetBool("plp", "add_c0"));
actualParams = &PLP;
break;
#endif // PHNREC_ONLY
default:
char msg[1024];
sprintf(msg, "Unknown parameterization (parameters/kind): '%s'\n", C.GetString("parameters", "kind"));
MERROR(msg);
return false;
}
// on-line normalization
MLOG(" - online normalization ...\n");
int interval = C.GetInt("onlinenorm", "estim_interval");
if(interval != 0)
Norm.StartEstimation(interval);
Norm.SetSignalEstimEnd(C.GetBool("onlinenorm", "signal_est_end"));
Norm.SetFile(C.GetString("onlinenorm", "file"));
Norm.SetMeanNorm(C.GetBool("onlinenorm", "mean_norm"));
Norm.SetVarNorm(C.GetBool("onlinenorm", "var_norm"));
Norm.SetScaleToGVar(C.GetBool("onlinenorm", "scale_to_gvar"));
// traps
MLOG(" - posteriors (loading NNs) ...\n");
if(!TR.SetSystem(C.GetString("posteriors", "system")))
{
char msg[1024];
sprintf(msg, "Unknown system, check configuration: %s", C.GetString("system", "type"));
MERROR(msg);
return false;
}
mTrapsEnabled = C.GetBool("posteriors", "enabled");
if(mTrapsEnabled)
{
TR.SetTrapLen(C.GetInt("posteriors", "length"));
TR.SetHamming(C.GetBool("posteriors", "hamming"));
TR.SetNBanks(C.GetInt("melbanks", "nbanks"));
TR.SetAddC0(C.GetBool("posteriors", "add_c0"));
bunchSize = C.GetInt("posteriors", "bunch_size");
TR.SetBunchSize(bunchSize);
TR.Init(config_dir); // loads nets and allocates memory
C.SetInt("posteriors", "noutputs", TR.GetNumOuts());
}
// decoder
MLOG(" - decoder ...\n\n");
DE = 0;
#ifndef PHNREC_ONLY
if(strcmp(C.GetString("decoder", "type"), "stkint") == 0)
{
DE = (Decoder *)new StkInterface;
((StkInterface *)DE)->ReadHMMSet(C.GetString("models", "hmm_defs"));
if(strcmp(C.GetString("networks", "default"), "none") != 0)
((StkInterface *)DE)->LoadNetwork(C.GetString("networks", "default"));
((StkInterface *)DE)->SetTimePruning(C.GetInt("decoder", "time_pruning"));
((StkInterface *)DE)->SetLMScale(C.GetFloat("decoder", "lm_scale"));
}
#endif // PHNREC_ONLY
if(strcmp(C.GetString("decoder", "type"), "phndec") == 0)
{
DE = (PhnDec *)new PhnDec;
((PhnDec *)DE)->SetNStPerPhn(C.GetInt("decoder", "num_states_per_phn"));
((PhnDec *)DE)->SetTimePruning(C.GetInt("decoder", "time_pruning"));
if(((PhnDec *)DE)->LoadPhnList(C.GetString("dicts", "phoneme_list")) != DECERR_NONE)
{
char msg[1024];
sprintf(msg, "Can not load phoneme list: %s", C.GetString("dicts", "phoneme_list"));
MERROR(msg);
return false;
}
}
if(DE == 0)
{
char msg[1024];
sprintf(msg, "Unknown dekoder, check configuration: %s", C.GetString("decoder", "type"));
MERROR(msg);
return false;
}
DE->SetWPenalty(C.GetFloat("decoder", "wpenalty"));
if(strcmp(C.GetString("decoder", "mode"), "kws") == 0)
DE->SetMode(DECMODE_KWS);
else
DE->SetMode(DECMODE_DECODE);
// softening functions
float a1, a2, a3;
soft_func func = Str2SoftFunc(C.GetString("posteriors", "softening_func"), &a1, &a2, &a3);
SetPostSoftFunc(func, a1, a2, a3);
func = Str2SoftFunc(C.GetString("decoder", "softening_func"), &a1, &a2, &a3);
SetDecSoftFunc(func, a1, a2, a3);
//MLOG("Initialization done.\n");
//MLOG("\n");
char msg[1024];
sprintf(msg, "------------------- SUMMARY -------------------\n" ); MLOG(msg);
sprintf(msg, "Dictionary: %s\n", C.GetString("dicts", "phoneme_list" )); MLOG(msg);
sprintf(msg, "Network file: %s\n", C.GetString("networks", "default" )); MLOG(msg);
sprintf(msg, "HMM file: %s\n", C.GetString("models", "hmm_defs" )); MLOG(msg);
sprintf(msg, "#States/Phn: %d\n", C.GetInt( "models", "nstates" )); MLOG(msg);
sprintf(msg, "Time pruning: %d\n", C.GetInt( "decoder", "time_pruning" )); MLOG(msg);
sprintf(msg, "Word penalty: %f\n", C.GetFloat( "decoder", "wpenalty" )); MLOG(msg);
sprintf(msg, "Soft func: %s\n", C.GetString("decoder", "softening_func")); MLOG(msg);
sprintf(msg, "-----------------------------------------------\n\n" ); MLOG(msg);
// memory buffers
if(params)
delete [] params;
if(posteriors)
delete [] posteriors;
int n = (TR.GetTrapShift() > bunchSize ? TR.GetTrapShift() : bunchSize);
params = new float [n * C.GetInt("melbanks", "nbanks")];
posteriors = new float [n * TR.GetNumOuts()];
return true;
}
bool SpeechRec::ConvertWaveformFormat(wave_format format, void *sig, int nBytes, float **buff, int *buffLen)
{
assert(format == wfLin16 || format == wfALaw);
int sigLen;
int i;
float *out;
if(buff == 0 || *buff == 0)
out = 0;
else
out = *buff;
switch(format)
{
case wfLin16:
sigLen = nBytes / sizeof(short);
if(!out || *buffLen != sigLen)
{
if(out)
delete [] out;
out = new float [sigLen > MB_VECTORSIZE ? sigLen : MB_VECTORSIZE];
if(!out)
{
MERROR("Insufficient memory\n");
return false;
}
}
for(i = 0; i < MB_VECTORSIZE; ++i) // this ensures at least one frame if the signal is too short
out[i] = 0.0f;
for(i = 0; i < sigLen; ++i)
out[i] = (float)((short *)sig)[i];
*buffLen = sigLen;
*buff = out;
break;
case wfALaw:
sigLen = nBytes;
if(!out || *buffLen != sigLen)
{
if(buff)
delete [] out;
out = new float [sigLen > MB_VECTORSIZE ? sigLen : MB_VECTORSIZE];
if(!out)
{
MERROR("Insufficient memory\n");
return false;
}
}
for(i = 0; i < MB_VECTORSIZE; ++i)
out[i] = 0.0f;
for(i = 0; i < sigLen; ++i)
out[i] = 8.0f * (float)ALawTableD5[((unsigned char *)sig)[i]];
*buffLen = sigLen;
*buff = out;
break;
case wfUnknown:
assert(0);
}
// shift DC of the waveform
if(waveDCShift != 0.0f)
sAddition(*buffLen, *buff, waveDCShift);
// scale the waweform
if(waveScale != 1.0f)
sMultiplication(*buffLen, *buff, waveScale);
if(waveNoiseLevel != 0.0f)
sAddNoise(*buffLen, *buff, waveNoiseLevel);
return true;
}
bool SpeechRec::ProcessOnline(void *inpSig, int sigNBytes, bool lastFrame)
{
if(!ConvertWaveformFormat(waveFormat, inpSig, sigNBytes, &waveform, &waveformLen))
return false;
actualParams->AddWaveform(waveform, waveformLen);
while(actualParams->GetFeatures(params + bunchIdx * actualParams->GetNParams()))
{
// minima thresholds etc.
FrameBasedNormalization(params + bunchIdx * actualParams->GetNParams(), actualParams->GetNParams());
// initial interval based mean and variance normalization
Norm.ProcessFrame(actualParams->GetNParams(), params + bunchIdx * actualParams->GetNParams());
lastParamVector = bunchIdx;
bunchIdx++;
if(bunchIdx == bunchSize)
{
if(mTrapsEnabled)
{
TR.CalcFeaturesBunched(params, posteriors, bunchSize);
// this function is split into two parts just becasuse of saving in off-line mode
int j;
for(j = 0; j < bunchSize * TR.GetNumOuts(); j++)
posteriors[j] = (*postSoftFunc)(posteriors[j], postSoftArg1, postSoftArg2, postSoftArg3);
for(j = 0; j < bunchSize * TR.GetNumOuts(); j++)
posteriors[j] = (*decSoftFunc)(posteriors[j], decSoftArg1, decSoftArg2, decSoftArg3);
int i;
for(i = 0; i < bunchSize; i++)
{
if(TR.GetDelay() >= TR.GetTrapShift()) // Initialization of TRAPS - skip half of the trap length
DE->ProcessFrame(posteriors + i * TR.GetNumOuts());
}
}
else
{
int i;
for(i = 0; i < bunchSize; i++)
{
DE->ProcessFrame(params + i * actualParams->GetNParams());
}
}
bunchIdx = 0;
}
}
if(lastFrame)
ProcessTail();
return true;
}
bool SpeechRec::ProcessLastBunch()
{
if(bunchIdx == 0)
return false;
TR.CalcFeaturesBunched(params, posteriors, bunchIdx);
int j;
for(j = 0; j < bunchIdx * TR.GetNumOuts(); j++)
posteriors[j] = (*postSoftFunc)(posteriors[j], postSoftArg1, postSoftArg2, postSoftArg3);
for(j = 0; j < bunchIdx * TR.GetNumOuts(); j++)
posteriors[j] = (*decSoftFunc)(posteriors[j], decSoftArg1, decSoftArg2, decSoftArg3);
int i;
for(i = 0; i < bunchIdx; i++)
{
if(TR.GetDelay() >= TR.GetTrapShift())
DE->ProcessFrame(posteriors + i * TR.GetNumOuts());
}
bunchIdx = 0;
return true;
}
bool SpeechRec::ProcessTail()
{
if(mTrapsEnabled)
{
ProcessLastBunch();
if(lastParamVector < 0)
return false;
int nparams = actualParams->GetNParams();
int tshift = TR.GetTrapShift();
// repeate last vector tshift times
int i;
for(i = 0; i < tshift; i++)
{
if(i != lastParamVector)
sCopy(nparams, params + i * nparams, params + lastParamVector * nparams);
}
TR.CalcFeaturesBunched(params, posteriors, tshift);
int j;
for(j = 0; j < tshift * TR.GetNumOuts(); j++)
posteriors[j] = (*postSoftFunc)(posteriors[j], postSoftArg1, postSoftArg2, postSoftArg3);
for(j = 0; j < tshift * TR.GetNumOuts(); j++)
posteriors[j] = (*decSoftFunc)(posteriors[j], decSoftArg1, decSoftArg2, decSoftArg3);
for(i = 0; i < tshift; i++)
{
if(TR.GetDelay() >= TR.GetTrapShift())
DE->ProcessFrame(posteriors + i * TR.GetNumOuts());
}
}
else
{
int i;
for(i = 0; i < bunchIdx; i++)
{
DE->ProcessFrame(params + i * actualParams->GetNParams());
}
}
bunchIdx = 0;
lastParamVector = -1;
return true;
}
bool SpeechRec::ProcessOffline(data_format inpf, data_format outpf, void *inpSig, int sigNBytes, Mat<float> *inpMat, Mat<float> *outMat)
{
assert((int)inpf < (int)outpf);
assert(outMat || outpf == dfStrings);
assert(inpMat || inpf == dfWaveform);
Mat<float> *paramMat = 0;
Mat<float> *posteriorsMat = 0;
// waveform -> parameters
int nFrames;
if(inpf == dfWaveform)
{
if(!ConvertWaveformFormat(waveFormat, inpSig, sigNBytes, &waveform, &waveformLen))
return false;
nFrames = (waveformLen > actualParams->GetVectorSize() ? (waveformLen - actualParams->GetVectorSize()) / actualParams->GetStep() + 1 : 1);
actualParams->AddWaveform(waveform, waveformLen);
if(outpf == dfParams)
{
paramMat = outMat;
}
else
{
paramMat = new Mat<float>;
if(!paramMat)
{
MERROR("Insufficient memory\n");
return false;
}
}
if(actualParams->GetNParams() != paramMat->columns() || nFrames != paramMat->rows())
paramMat->init(nFrames, actualParams->GetNParams());
int fr = 0;
while(actualParams->GetFeatures(params))
{
FrameBasedNormalization(params, actualParams->GetNParams());
paramMat->set(fr, fr, 0, actualParams->GetNParams() - 1, params);
fr++;
}
if(outpf == dfParams)
return true;
}
// sentence based normalization
if(inpf == dfWaveform || inpf == dfParams)
{
if(inpf == dfParams)
paramMat = inpMat;
if(paramMat->columns() < actualParams->GetNParams())
{
MERROR("Invalid dimensionality of parameter vectors\n");
return false;
}
else if(paramMat->columns() > actualParams->GetNParams())
{
Mat<float> *tmpMat = new Mat<float>;
tmpMat->init(paramMat->rows(), actualParams->GetNParams());
tmpMat->copy(*paramMat, 0, paramMat->rows() - 1, 0, actualParams->GetNParams() - 1,
0, paramMat->rows() - 1, 0, actualParams->GetNParams() - 1);
delete paramMat;
paramMat = tmpMat;
inpMat = paramMat;
}
SentenceBasedNormalization(paramMat);
}