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Support GigaAM CTC models for Russian ASR (#1464)

Browse Source 
See also https://github.com/salute-developers/GigaAM
This commit is contained in:
Fangjun Kuang
2024-10-25 10:55:16 +08:00
committed by GitHub
parent 2b40079faf
commit b41f6d2c94
24 changed files with 641 additions and 160 deletions
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2
sherpa-onnx/csrc/features.cc
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@@ -193,6 +193,7 @@ class FeatureExtractor::Impl {
opts_.frame_opts.frame_shift_ms = config_.frame_shift_ms;
opts_.frame_opts.frame_length_ms = config_.frame_length_ms;
opts_.frame_opts.remove_dc_offset = config_.remove_dc_offset;
opts_.frame_opts.preemph_coeff = config_.preemph_coeff;
opts_.frame_opts.window_type = config_.window_type;
opts_.mel_opts.num_bins = config_.feature_dim;
@@ -211,6 +212,7 @@ class FeatureExtractor::Impl {
mfcc_opts_.frame_opts.frame_shift_ms = config_.frame_shift_ms;
mfcc_opts_.frame_opts.frame_length_ms = config_.frame_length_ms;
mfcc_opts_.frame_opts.remove_dc_offset = config_.remove_dc_offset;
mfcc_opts_.frame_opts.preemph_coeff = config_.preemph_coeff;
mfcc_opts_.frame_opts.window_type = config_.window_type;
mfcc_opts_.mel_opts.num_bins = config_.feature_dim;

1
sherpa-onnx/csrc/features.h
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@@ -57,6 +57,7 @@ struct FeatureExtractorConfig {
float frame_length_ms = 25.0f; // in milliseconds.
bool is_librosa = false;
bool remove_dc_offset = true; // Subtract mean of wave before FFT.
float preemph_coeff = 0.97f; // Preemphasis coefficient.
std::string window_type = "povey"; // e.g. Hamming window
// For models from NeMo

2
sherpa-onnx/csrc/jieba-lexicon.cc
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@@ -10,8 +10,8 @@
#include "cppjieba/Jieba.hpp"
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/lexicon.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/symbol-table.h"
#include "sherpa-onnx/csrc/text-utils.h"
namespace sherpa_onnx {

40
sherpa-onnx/csrc/lexicon.cc
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@@ -21,6 +21,7 @@
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/symbol-table.h"
#include "sherpa-onnx/csrc/text-utils.h"
namespace sherpa_onnx {
@@ -74,45 +75,6 @@ static std::vector<std::string> ProcessHeteronyms(
return ans;
}
// Note: We don't use SymbolTable here since tokens may contain a blank
// in the first column
std::unordered_map<std::string, int32_t> ReadTokens(std::istream &is) {
std::unordered_map<std::string, int32_t> token2id;
std::string line;
std::string sym;
int32_t id = -1;
while (std::getline(is, line)) {
std::istringstream iss(line);
iss >> sym;
if (iss.eof()) {
id = atoi(sym.c_str());
sym = " ";
} else {
iss >> id;
}
// eat the trailing \r\n on windows
iss >> std::ws;
if (!iss.eof()) {
SHERPA_ONNX_LOGE("Error: %s", line.c_str());
exit(-1);
}
#if 0
if (token2id.count(sym)) {
SHERPA_ONNX_LOGE("Duplicated token %s. Line %s. Existing ID: %d",
sym.c_str(), line.c_str(), token2id.at(sym));
exit(-1);
}
#endif
token2id.insert({std::move(sym), id});
}
return token2id;
}
std::vector<int32_t> ConvertTokensToIds(
const std::unordered_map<std::string, int32_t> &token2id,
const std::vector<std::string> &tokens) {

6
sherpa-onnx/csrc/lexicon.h
View File

@@ -67,12 +67,6 @@ class Lexicon : public OfflineTtsFrontend {
bool debug_ = false;
};
std::unordered_map<std::string, int32_t> ReadTokens(std::istream &is);
std::vector<int32_t> ConvertTokensToIds(
const std::unordered_map<std::string, int32_t> &token2id,
const std::vector<std::string> &tokens);
} // namespace sherpa_onnx
#endif // SHERPA_ONNX_CSRC_LEXICON_H_

140
sherpa-onnx/csrc/macros.h
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@@ -41,13 +41,13 @@
auto value = \
meta_data.LookupCustomMetadataMapAllocated(src_key, allocator); \
if (!value) { \
SHERPA_ONNX_LOGE("%s does not exist in the metadata", src_key); \
SHERPA_ONNX_LOGE("'%s' does not exist in the metadata", src_key); \
exit(-1); \
} \
\
dst = atoi(value.get()); \
if (dst < 0) { \
SHERPA_ONNX_LOGE("Invalid value %d for %s", dst, src_key); \
SHERPA_ONNX_LOGE("Invalid value %d for '%s'", dst, src_key); \
exit(-1); \
} \
} while (0)
@@ -61,80 +61,80 @@
} else { \
dst = atoi(value.get()); \
if (dst < 0) { \
SHERPA_ONNX_LOGE("Invalid value %d for %s", dst, src_key); \
SHERPA_ONNX_LOGE("Invalid value %d for '%s'", dst, src_key); \
exit(-1); \
} \
} \
} while (0)
// read a vector of integers
#define SHERPA_ONNX_READ_META_DATA_VEC(dst, src_key) \
do { \
auto value = \
meta_data.LookupCustomMetadataMapAllocated(src_key, allocator); \
if (!value) { \
SHERPA_ONNX_LOGE("%s does not exist in the metadata", src_key); \
exit(-1); \
} \
\
bool ret = SplitStringToIntegers(value.get(), ",", true, &dst); \
if (!ret) { \
SHERPA_ONNX_LOGE("Invalid value %s for %s", value.get(), src_key); \
exit(-1); \
} \
#define SHERPA_ONNX_READ_META_DATA_VEC(dst, src_key) \
do { \
auto value = \
meta_data.LookupCustomMetadataMapAllocated(src_key, allocator); \
if (!value) { \
SHERPA_ONNX_LOGE("'%s' does not exist in the metadata", src_key); \
exit(-1); \
} \
\
bool ret = SplitStringToIntegers(value.get(), ",", true, &dst); \
if (!ret) { \
SHERPA_ONNX_LOGE("Invalid value '%s' for '%s'", value.get(), src_key); \
exit(-1); \
} \
} while (0)
// read a vector of floats
#define SHERPA_ONNX_READ_META_DATA_VEC_FLOAT(dst, src_key) \
do { \
auto value = \
meta_data.LookupCustomMetadataMapAllocated(src_key, allocator); \
if (!value) { \
SHERPA_ONNX_LOGE("%s does not exist in the metadata", src_key); \
exit(-1); \
} \
\
bool ret = SplitStringToFloats(value.get(), ",", true, &dst); \
if (!ret) { \
SHERPA_ONNX_LOGE("Invalid value %s for %s", value.get(), src_key); \
exit(-1); \
} \
#define SHERPA_ONNX_READ_META_DATA_VEC_FLOAT(dst, src_key) \
do { \
auto value = \
meta_data.LookupCustomMetadataMapAllocated(src_key, allocator); \
if (!value) { \
SHERPA_ONNX_LOGE("%s does not exist in the metadata", src_key); \
exit(-1); \
} \
\
bool ret = SplitStringToFloats(value.get(), ",", true, &dst); \
if (!ret) { \
SHERPA_ONNX_LOGE("Invalid value '%s' for '%s'", value.get(), src_key); \
exit(-1); \
} \
} while (0)
// read a vector of strings
#define SHERPA_ONNX_READ_META_DATA_VEC_STRING(dst, src_key) \
do { \
auto value = \
meta_data.LookupCustomMetadataMapAllocated(src_key, allocator); \
if (!value) { \
SHERPA_ONNX_LOGE("%s does not exist in the metadata", src_key); \
exit(-1); \
} \
SplitStringToVector(value.get(), ",", false, &dst); \
\
if (dst.empty()) { \
SHERPA_ONNX_LOGE("Invalid value %s for %s. Empty vector!", value.get(), \
src_key); \
exit(-1); \
} \
#define SHERPA_ONNX_READ_META_DATA_VEC_STRING(dst, src_key) \
do { \
auto value = \
meta_data.LookupCustomMetadataMapAllocated(src_key, allocator); \
if (!value) { \
SHERPA_ONNX_LOGE("'%s' does not exist in the metadata", src_key); \
exit(-1); \
} \
SplitStringToVector(value.get(), ",", false, &dst); \
\
if (dst.empty()) { \
SHERPA_ONNX_LOGE("Invalid value '%s' for '%s'. Empty vector!", \
value.get(), src_key); \
exit(-1); \
} \
} while (0)
// read a vector of strings separated by sep
#define SHERPA_ONNX_READ_META_DATA_VEC_STRING_SEP(dst, src_key, sep) \
do { \
auto value = \
meta_data.LookupCustomMetadataMapAllocated(src_key, allocator); \
if (!value) { \
SHERPA_ONNX_LOGE("%s does not exist in the metadata", src_key); \
exit(-1); \
} \
SplitStringToVector(value.get(), sep, false, &dst); \
\
if (dst.empty()) { \
SHERPA_ONNX_LOGE("Invalid value %s for %s. Empty vector!", value.get(), \
src_key); \
exit(-1); \
} \
#define SHERPA_ONNX_READ_META_DATA_VEC_STRING_SEP(dst, src_key, sep) \
do { \
auto value = \
meta_data.LookupCustomMetadataMapAllocated(src_key, allocator); \
if (!value) { \
SHERPA_ONNX_LOGE("'%s' does not exist in the metadata", src_key); \
exit(-1); \
} \
SplitStringToVector(value.get(), sep, false, &dst); \
\
if (dst.empty()) { \
SHERPA_ONNX_LOGE("Invalid value '%s' for '%s'. Empty vector!", \
value.get(), src_key); \
exit(-1); \
} \
} while (0)
// Read a string
@@ -143,17 +143,29 @@
auto value = \
meta_data.LookupCustomMetadataMapAllocated(src_key, allocator); \
if (!value) { \
SHERPA_ONNX_LOGE("%s does not exist in the metadata", src_key); \
SHERPA_ONNX_LOGE("'%s' does not exist in the metadata", src_key); \
exit(-1); \
} \
\
dst = value.get(); \
if (dst.empty()) { \
SHERPA_ONNX_LOGE("Invalid value for %s\n", src_key); \
SHERPA_ONNX_LOGE("Invalid value for '%s'\n", src_key); \
exit(-1); \
} \
} while (0)
#define SHERPA_ONNX_READ_META_DATA_STR_ALLOW_EMPTY(dst, src_key) \
do { \
auto value = \
meta_data.LookupCustomMetadataMapAllocated(src_key, allocator); \
if (!value) { \
SHERPA_ONNX_LOGE("'%s' does not exist in the metadata", src_key); \
exit(-1); \
} \
\
dst = value.get(); \
} while (0)
#define SHERPA_ONNX_READ_META_DATA_STR_WITH_DEFAULT(dst, src_key, \
default_value) \
do { \
@@ -164,7 +176,7 @@
} else { \
dst = value.get(); \
if (dst.empty()) { \
SHERPA_ONNX_LOGE("Invalid value for %s\n", src_key); \
SHERPA_ONNX_LOGE("Invalid value for '%s'\n", src_key); \
exit(-1); \
} \
} \

2
sherpa-onnx/csrc/melo-tts-lexicon.cc
View File

@@ -10,8 +10,8 @@
#include "cppjieba/Jieba.hpp"
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/lexicon.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/symbol-table.h"
#include "sherpa-onnx/csrc/text-utils.h"
namespace sherpa_onnx {

19
sherpa-onnx/csrc/offline-ctc-model.cc
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@@ -21,6 +21,7 @@ namespace {
enum class ModelType : std::uint8_t {
kEncDecCTCModelBPE,
kEncDecCTCModel,
kEncDecHybridRNNTCTCBPEModel,
kTdnn,
kZipformerCtc,
@@ -75,6 +76,8 @@ static ModelType GetModelType(char *model_data, size_t model_data_length,
if (model_type.get() == std::string("EncDecCTCModelBPE")) {
return ModelType::kEncDecCTCModelBPE;
} else if (model_type.get() == std::string("EncDecCTCModel")) {
return ModelType::kEncDecCTCModel;
} else if (model_type.get() == std::string("EncDecHybridRNNTCTCBPEModel")) {
return ModelType::kEncDecHybridRNNTCTCBPEModel;
} else if (model_type.get() == std::string("tdnn")) {
@@ -121,22 +124,18 @@ std::unique_ptr<OfflineCtcModel> OfflineCtcModel::Create(
switch (model_type) {
case ModelType::kEncDecCTCModelBPE:
return std::make_unique<OfflineNemoEncDecCtcModel>(config);
break;
case ModelType::kEncDecCTCModel:
return std::make_unique<OfflineNemoEncDecCtcModel>(config);
case ModelType::kEncDecHybridRNNTCTCBPEModel:
return std::make_unique<OfflineNemoEncDecHybridRNNTCTCBPEModel>(config);
break;
case ModelType::kTdnn:
return std::make_unique<OfflineTdnnCtcModel>(config);
break;
case ModelType::kZipformerCtc:
return std::make_unique<OfflineZipformerCtcModel>(config);
break;
case ModelType::kWenetCtc:
return std::make_unique<OfflineWenetCtcModel>(config);
break;
case ModelType::kTeleSpeechCtc:
return std::make_unique<OfflineTeleSpeechCtcModel>(config);
break;
case ModelType::kUnknown:
SHERPA_ONNX_LOGE("Unknown model type in offline CTC!");
return nullptr;
@@ -177,23 +176,19 @@ std::unique_ptr<OfflineCtcModel> OfflineCtcModel::Create(
switch (model_type) {
case ModelType::kEncDecCTCModelBPE:
return std::make_unique<OfflineNemoEncDecCtcModel>(mgr, config);
break;
case ModelType::kEncDecCTCModel:
return std::make_unique<OfflineNemoEncDecCtcModel>(mgr, config);
case ModelType::kEncDecHybridRNNTCTCBPEModel:
return std::make_unique<OfflineNemoEncDecHybridRNNTCTCBPEModel>(mgr,
config);
break;
case ModelType::kTdnn:
return std::make_unique<OfflineTdnnCtcModel>(mgr, config);
break;
case ModelType::kZipformerCtc:
return std::make_unique<OfflineZipformerCtcModel>(mgr, config);
break;
case ModelType::kWenetCtc:
return std::make_unique<OfflineWenetCtcModel>(mgr, config);
break;
case ModelType::kTeleSpeechCtc:
return std::make_unique<OfflineTeleSpeechCtcModel>(mgr, config);
break;
case ModelType::kUnknown:
SHERPA_ONNX_LOGE("Unknown model type in offline CTC!");
return nullptr;

4
sherpa-onnx/csrc/offline-ctc-model.h
View File

@@ -66,6 +66,10 @@ class OfflineCtcModel {
// Return true if the model supports batch size > 1
virtual bool SupportBatchProcessing() const { return true; }
// return true for models from https://github.com/salute-developers/GigaAM
// return false otherwise
virtual bool IsGigaAM() const { return false; }
};
} // namespace sherpa_onnx

12
sherpa-onnx/csrc/offline-nemo-enc-dec-ctc-model.cc
View File

@@ -72,6 +72,8 @@ class OfflineNemoEncDecCtcModel::Impl {
std::string FeatureNormalizationMethod() const { return normalize_type_; }
bool IsGigaAM() const { return is_giga_am_; }
private:
void Init(void *model_data, size_t model_data_length) {
sess_ = std::make_unique<Ort::Session>(env_, model_data, model_data_length,
@@ -92,7 +94,9 @@ class OfflineNemoEncDecCtcModel::Impl {
Ort::AllocatorWithDefaultOptions allocator; // used in the macro below
SHERPA_ONNX_READ_META_DATA(vocab_size_, "vocab_size");
SHERPA_ONNX_READ_META_DATA(subsampling_factor_, "subsampling_factor");
SHERPA_ONNX_READ_META_DATA_STR(normalize_type_, "normalize_type");
SHERPA_ONNX_READ_META_DATA_STR_ALLOW_EMPTY(normalize_type_,
"normalize_type");
SHERPA_ONNX_READ_META_DATA_WITH_DEFAULT(is_giga_am_, "is_giga_am", 0);
}
private:
@@ -112,6 +116,10 @@ class OfflineNemoEncDecCtcModel::Impl {
int32_t vocab_size_ = 0;
int32_t subsampling_factor_ = 0;
std::string normalize_type_;
// it is 1 for models from
// https://github.com/salute-developers/GigaAM
int32_t is_giga_am_ = 0;
};
OfflineNemoEncDecCtcModel::OfflineNemoEncDecCtcModel(
@@ -146,4 +154,6 @@ std::string OfflineNemoEncDecCtcModel::FeatureNormalizationMethod() const {
return impl_->FeatureNormalizationMethod();
}
bool OfflineNemoEncDecCtcModel::IsGigaAM() const { return impl_->IsGigaAM(); }
} // namespace sherpa_onnx

2
sherpa-onnx/csrc/offline-nemo-enc-dec-ctc-model.h
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@@ -76,6 +76,8 @@ class OfflineNemoEncDecCtcModel : public OfflineCtcModel {
// for details
std::string FeatureNormalizationMethod() const override;
bool IsGigaAM() const override;
private:
class Impl;
std::unique_ptr<Impl> impl_;

19
sherpa-onnx/csrc/offline-recognizer-ctc-impl.h
View File

@@ -104,11 +104,20 @@ class OfflineRecognizerCtcImpl : public OfflineRecognizerImpl {
}
if (!config_.model_config.nemo_ctc.model.empty()) {
config_.feat_config.low_freq = 0;
config_.feat_config.high_freq = 0;
config_.feat_config.is_librosa = true;
config_.feat_config.remove_dc_offset = false;
config_.feat_config.window_type = "hann";
if (model_->IsGigaAM()) {
config_.feat_config.low_freq = 0;
config_.feat_config.high_freq = 8000;
config_.feat_config.remove_dc_offset = false;
config_.feat_config.preemph_coeff = 0;
config_.feat_config.window_type = "hann";
config_.feat_config.feature_dim = 64;
} else {
config_.feat_config.low_freq = 0;
config_.feat_config.high_freq = 0;
config_.feat_config.is_librosa = true;
config_.feat_config.remove_dc_offset = false;
config_.feat_config.window_type = "hann";
}
}
if (!config_.model_config.wenet_ctc.model.empty()) {

6
sherpa-onnx/csrc/offline-recognizer-impl.cc
View File

@@ -172,7 +172,7 @@ std::unique_ptr<OfflineRecognizerImpl> OfflineRecognizerImpl::Create(
return std::make_unique<OfflineRecognizerTransducerNeMoImpl>(config);
}
if (model_type == "EncDecCTCModelBPE" ||
if (model_type == "EncDecCTCModelBPE" || model_type == "EncDecCTCModel" ||
model_type == "EncDecHybridRNNTCTCBPEModel" || model_type == "tdnn" ||
model_type == "zipformer2_ctc" || model_type == "wenet_ctc" ||
model_type == "telespeech_ctc") {
@@ -189,6 +189,7 @@ std::unique_ptr<OfflineRecognizerImpl> OfflineRecognizerImpl::Create(
" - Non-streaming transducer models from icefall\n"
" - Non-streaming Paraformer models from FunASR\n"
" - EncDecCTCModelBPE models from NeMo\n"
" - EncDecCTCModel models from NeMo\n"
" - EncDecHybridRNNTCTCBPEModel models from NeMo\n"
" - Whisper models\n"
" - Tdnn models\n"
@@ -343,7 +344,7 @@ std::unique_ptr<OfflineRecognizerImpl> OfflineRecognizerImpl::Create(
return std::make_unique<OfflineRecognizerTransducerNeMoImpl>(mgr, config);
}
if (model_type == "EncDecCTCModelBPE" ||
if (model_type == "EncDecCTCModelBPE" || model_type == "EncDecCTCModel" ||
model_type == "EncDecHybridRNNTCTCBPEModel" || model_type == "tdnn" ||
model_type == "zipformer2_ctc" || model_type == "wenet_ctc" ||
model_type == "telespeech_ctc") {
@@ -360,6 +361,7 @@ std::unique_ptr<OfflineRecognizerImpl> OfflineRecognizerImpl::Create(
" - Non-streaming transducer models from icefall\n"
" - Non-streaming Paraformer models from FunASR\n"
" - EncDecCTCModelBPE models from NeMo\n"
" - EncDecCTCModel models from NeMo\n"
" - EncDecHybridRNNTCTCBPEModel models from NeMo\n"
" - Whisper models\n"
" - Tdnn models\n"

66
sherpa-onnx/csrc/symbol-table.cc
View File

@@ -7,6 +7,8 @@
#include <cassert>
#include <fstream>
#include <sstream>
#include <string>
#include <utility>
#if __ANDROID_API__ >= 9
#include <strstream>
@@ -16,10 +18,54 @@
#endif
#include "sherpa-onnx/csrc/base64-decode.h"
#include "sherpa-onnx/csrc/lexicon.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
namespace sherpa_onnx {
std::unordered_map<std::string, int32_t> ReadTokens(
std::istream &is,
std::unordered_map<int32_t, std::string> *id2token /*= nullptr*/) {
std::unordered_map<std::string, int32_t> token2id;
std::string line;
std::string sym;
int32_t id = -1;
while (std::getline(is, line)) {
std::istringstream iss(line);
iss >> sym;
if (iss.eof()) {
id = atoi(sym.c_str());
sym = " ";
} else {
iss >> id;
}
// eat the trailing \r\n on windows
iss >> std::ws;
if (!iss.eof()) {
SHERPA_ONNX_LOGE("Error: %s", line.c_str());
exit(-1);
}
#if 0
if (token2id.count(sym)) {
SHERPA_ONNX_LOGE("Duplicated token %s. Line %s. Existing ID: %d",
sym.c_str(), line.c_str(), token2id.at(sym));
exit(-1);
}
#endif
if (id2token) {
id2token->insert({id, sym});
}
token2id.insert({std::move(sym), id});
}
return token2id;
}
SymbolTable::SymbolTable(const std::string &filename, bool is_file) {
if (is_file) {
std::ifstream is(filename);
@@ -39,25 +85,7 @@ SymbolTable::SymbolTable(AAssetManager *mgr, const std::string &filename) {
}
#endif
void SymbolTable::Init(std::istream &is) {
std::string sym;
int32_t id = 0;
while (is >> sym >> id) {
#if 0
// we disable the test here since for some multi-lingual BPE models
// from NeMo, the same symbol can appear multiple times with different IDs.
if (sym != " ") {
assert(sym2id_.count(sym) == 0);
}
#endif
assert(id2sym_.count(id) == 0);
sym2id_.insert({sym, id});
id2sym_.insert({id, sym});
}
assert(is.eof());
}
void SymbolTable::Init(std::istream &is) { sym2id_ = ReadTokens(is, &id2sym_); }
std::string SymbolTable::ToString() const {
std::ostringstream os;

12
sherpa-onnx/csrc/symbol-table.h
View File

@@ -5,8 +5,10 @@
#ifndef SHERPA_ONNX_CSRC_SYMBOL_TABLE_H_
#define SHERPA_ONNX_CSRC_SYMBOL_TABLE_H_
#include <istream>
#include <string>
#include <unordered_map>
#include <vector>
#if __ANDROID_API__ >= 9
#include "android/asset_manager.h"
@@ -15,6 +17,16 @@
namespace sherpa_onnx {
// The same token can be mapped to different integer IDs, so
// we need an id2token argument here.
std::unordered_map<std::string, int32_t> ReadTokens(
std::istream &is,
std::unordered_map<int32_t, std::string> *id2token = nullptr);
std::vector<int32_t> ConvertTokensToIds(
const std::unordered_map<std::string, int32_t> &token2id,
const std::vector<std::string> &tokens);
/// It manages mapping between symbols and integer IDs.
class SymbolTable {
public:

10
sherpa-onnx/kotlin-api/OfflineRecognizer.kt
View File

@@ -394,6 +394,16 @@ fun getOfflineModelConfig(type: Int): OfflineModelConfig? {
modelType = "transducer",
)
}
19 -> {
val modelDir = "sherpa-onnx-nemo-ctc-giga-am-russian-2024-10-24"
return OfflineModelConfig(
nemo = OfflineNemoEncDecCtcModelConfig(
model = "$modelDir/model.int8.onnx",
),
tokens = "$modelDir/tokens.txt",
)
}
}
return null
}