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Use piper-phonemize to convert text to token IDs (#453)

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This commit is contained in:
Fangjun Kuang
2023-11-30 23:57:43 +08:00
committed by GitHub
parent db41778e99
commit 62dc3c3e46
55 changed files with 1048 additions and 192 deletions
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1
sherpa-onnx/csrc/CMakeLists.txt
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@@ -74,6 +74,7 @@ set(sources
packed-sequence.cc
pad-sequence.cc
parse-options.cc
piper-phonemize-lexicon.cc
provider.cc
resample.cc
session.cc

12
sherpa-onnx/csrc/lexicon.cc
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@@ -129,8 +129,8 @@ Lexicon::Lexicon(AAssetManager *mgr, const std::string &lexicon,
}
#endif
std::vector<int64_t> Lexicon::ConvertTextToTokenIds(
const std::string &text) const {
std::vector<std::vector<int64_t>> Lexicon::ConvertTextToTokenIds(
const std::string &text, const std::string & /*voice*/ /*= ""*/) const {
switch (language_) {
case Language::kEnglish:
return ConvertTextToTokenIdsEnglish(text);
@@ -150,7 +150,7 @@ std::vector<int64_t> Lexicon::ConvertTextToTokenIds(
return {};
}
std::vector<int64_t> Lexicon::ConvertTextToTokenIdsChinese(
std::vector<std::vector<int64_t>> Lexicon::ConvertTextToTokenIdsChinese(
const std::string &text) const {
std::vector<std::string> words;
if (pattern_) {
@@ -245,10 +245,10 @@ std::vector<int64_t> Lexicon::ConvertTextToTokenIdsChinese(
ans.push_back(eos);
}
return ans;
return {ans};
}
std::vector<int64_t> Lexicon::ConvertTextToTokenIdsEnglish(
std::vector<std::vector<int64_t>> Lexicon::ConvertTextToTokenIdsEnglish(
const std::string &_text) const {
std::string text(_text);
ToLowerCase(&text);
@@ -301,7 +301,7 @@ std::vector<int64_t> Lexicon::ConvertTextToTokenIdsEnglish(
ans.push_back(token2id_.at("$")); // eos
}
return ans;
return {ans};
}
void Lexicon::InitTokens(std::istream &is) { token2id_ = ReadTokens(is); }

21
sherpa-onnx/csrc/lexicon.h
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@@ -18,11 +18,15 @@
#include "android/asset_manager_jni.h"
#endif
#include "sherpa-onnx/csrc/offline-tts-frontend.h"
namespace sherpa_onnx {
// TODO(fangjun): Refactor it to an abstract class
class Lexicon {
class Lexicon : public OfflineTtsFrontend {
public:
Lexicon() = default; // for subclasses
//
// Note: for models from piper, we won't use this class.
Lexicon(const std::string &lexicon, const std::string &tokens,
const std::string &punctuations, const std::string &language,
bool debug = false, bool is_piper = false);
@@ -34,28 +38,29 @@ class Lexicon {
bool is_piper = false);
#endif
std::vector<int64_t> ConvertTextToTokenIds(const std::string &text) const;
std::vector<std::vector<int64_t>> ConvertTextToTokenIds(
const std::string &text, const std::string &voice = "") const override;
private:
std::vector<int64_t> ConvertTextToTokenIdsGerman(
std::vector<std::vector<int64_t>> ConvertTextToTokenIdsGerman(
const std::string &text) const {
return ConvertTextToTokenIdsEnglish(text);
}
std::vector<int64_t> ConvertTextToTokenIdsSpanish(
std::vector<std::vector<int64_t>> ConvertTextToTokenIdsSpanish(
const std::string &text) const {
return ConvertTextToTokenIdsEnglish(text);
}
std::vector<int64_t> ConvertTextToTokenIdsFrench(
std::vector<std::vector<int64_t>> ConvertTextToTokenIdsFrench(
const std::string &text) const {
return ConvertTextToTokenIdsEnglish(text);
}
std::vector<int64_t> ConvertTextToTokenIdsEnglish(
std::vector<std::vector<int64_t>> ConvertTextToTokenIdsEnglish(
const std::string &text) const;
std::vector<int64_t> ConvertTextToTokenIdsChinese(
std::vector<std::vector<int64_t>> ConvertTextToTokenIdsChinese(
const std::string &text) const;
void InitLanguage(const std::string &lang);

31
sherpa-onnx/csrc/macros.h
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@@ -43,6 +43,21 @@
} \
} while (0)
#define SHERPA_ONNX_READ_META_DATA_WITH_DEFAULT(dst, src_key, default_value) \
do { \
auto value = \
meta_data.LookupCustomMetadataMapAllocated(src_key, allocator); \
if (!value) { \
dst = default_value; \
} else { \
dst = atoi(value.get()); \
if (dst < 0) { \
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 { \
@@ -112,4 +127,20 @@
} \
} while (0)
#define SHERPA_ONNX_READ_META_DATA_STR_WITH_DEFAULT(dst, src_key, \
default_value) \
do { \
auto value = \
meta_data.LookupCustomMetadataMapAllocated(src_key, allocator); \
if (!value) { \
dst = default_value; \
} else { \
dst = value.get(); \
if (dst.empty()) { \
SHERPA_ONNX_LOGE("Invalid value for %s\n", src_key); \
exit(-1); \
} \
} \
} while (0)
#endif // SHERPA_ONNX_CSRC_MACROS_H_

35
sherpa-onnx/csrc/offline-tts-frontend.h Normal file
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@@ -0,0 +1,35 @@
// sherpa-onnx/csrc/offline-tts-frontend.h
//
// Copyright (c) 2023 Xiaomi Corporation
#ifndef SHERPA_ONNX_CSRC_OFFLINE_TTS_FRONTEND_H_
#define SHERPA_ONNX_CSRC_OFFLINE_TTS_FRONTEND_H_
#include <cstdint>
#include <string>
#include <vector>
namespace sherpa_onnx {
class OfflineTtsFrontend {
public:
virtual ~OfflineTtsFrontend() = default;
/** Convert a string to token IDs.
*
* @param text The input text.
* Example 1: "This is the first sample sentence; this is the
* second one." Example 2: "这是第一句。这是第二句。"
* @param voice Optional. It is for espeak-ng.
*
* @return Return a vector-of-vector of token IDs. Each subvector contains
* a sentence that can be processed independently.
* If a frontend does not support splitting the text into sentences,
* the resulting vector contains only one subvector.
*/
virtual std::vector<std::vector<int64_t>> ConvertTextToTokenIds(
const std::string &text, const std::string &voice = "") const = 0;
};
} // namespace sherpa_onnx
#endif // SHERPA_ONNX_CSRC_OFFLINE_TTS_FRONTEND_H_

135
sherpa-onnx/csrc/offline-tts-vits-impl.h
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@@ -18,9 +18,11 @@
#include "kaldifst/csrc/text-normalizer.h"
#include "sherpa-onnx/csrc/lexicon.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/offline-tts-frontend.h"
#include "sherpa-onnx/csrc/offline-tts-impl.h"
#include "sherpa-onnx/csrc/offline-tts-vits-model.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/piper-phonemize-lexicon.h"
#include "sherpa-onnx/csrc/text-utils.h"
namespace sherpa_onnx {
@@ -29,10 +31,9 @@ class OfflineTtsVitsImpl : public OfflineTtsImpl {
public:
explicit OfflineTtsVitsImpl(const OfflineTtsConfig &config)
: config_(config),
model_(std::make_unique<OfflineTtsVitsModel>(config.model)),
lexicon_(config.model.vits.lexicon, config.model.vits.tokens,
model_->Punctuations(), model_->Language(), config.model.debug,
model_->IsPiper()) {
model_(std::make_unique<OfflineTtsVitsModel>(config.model)) {
InitFrontend();
if (!config.rule_fsts.empty()) {
std::vector<std::string> files;
SplitStringToVector(config.rule_fsts, ",", false, &files);
@@ -49,10 +50,9 @@ class OfflineTtsVitsImpl : public OfflineTtsImpl {
#if __ANDROID_API__ >= 9
OfflineTtsVitsImpl(AAssetManager *mgr, const OfflineTtsConfig &config)
: config_(config),
model_(std::make_unique<OfflineTtsVitsModel>(mgr, config.model)),
lexicon_(mgr, config.model.vits.lexicon, config.model.vits.tokens,
model_->Punctuations(), model_->Language(), config.model.debug,
model_->IsPiper()) {
model_(std::make_unique<OfflineTtsVitsModel>(mgr, config.model)) {
InitFrontend(mgr);
if (!config.rule_fsts.empty()) {
std::vector<std::string> files;
SplitStringToVector(config.rule_fsts, ",", false, &files);
@@ -101,20 +101,119 @@ class OfflineTtsVitsImpl : public OfflineTtsImpl {
}
}
std::vector<int64_t> x = lexicon_.ConvertTextToTokenIds(text);
if (x.empty()) {
std::vector<std::vector<int64_t>> x =
frontend_->ConvertTextToTokenIds(text, model_->Voice());
if (x.empty() || (x.size() == 1 && x[0].empty())) {
SHERPA_ONNX_LOGE("Failed to convert %s to token IDs", text.c_str());
return {};
}
if (model_->AddBlank()) {
std::vector<int64_t> buffer(x.size() * 2 + 1);
int32_t i = 1;
for (auto k : x) {
buffer[i] = k;
i += 2;
if (model_->AddBlank() && config_.model.vits.data_dir.empty()) {
for (auto &k : x) {
k = AddBlank(k);
}
x = std::move(buffer);
}
int32_t x_size = static_cast<int32_t>(x.size());
if (config_.max_num_sentences <= 0 || x_size <= config_.max_num_sentences) {
return Process(x, sid, speed);
}
// the input text is too long, we process sentences within it in batches
// to avoid OOM. Batch size is config_.max_num_sentences
std::vector<std::vector<int64_t>> batch;
int32_t batch_size = config_.max_num_sentences;
batch.reserve(config_.max_num_sentences);
int32_t num_batches = x_size / batch_size;
if (config_.model.debug) {
SHERPA_ONNX_LOGE(
"Text is too long. Split it into %d batches. batch size: %d. Number "
"of sentences: %d",
num_batches, batch_size, x_size);
}
GeneratedAudio ans;
int32_t k = 0;
for (int32_t b = 0; b != num_batches; ++b) {
batch.clear();
for (int32_t i = 0; i != batch_size; ++i, ++k) {
batch.push_back(std::move(x[k]));
}
auto audio = Process(batch, sid, speed);
ans.sample_rate = audio.sample_rate;
ans.samples.insert(ans.samples.end(), audio.samples.begin(),
audio.samples.end());
}
batch.clear();
while (k < x.size()) {
batch.push_back(std::move(x[k]));
++k;
}
if (!batch.empty()) {
auto audio = Process(batch, sid, speed);
ans.sample_rate = audio.sample_rate;
ans.samples.insert(ans.samples.end(), audio.samples.begin(),
audio.samples.end());
}
return ans;
}
private:
void InitFrontend(AAssetManager *mgr) {
if (model_->IsPiper() && !config_.model.vits.data_dir.empty()) {
frontend_ = std::make_unique<PiperPhonemizeLexicon>(
mgr, config_.model.vits.tokens, config_.model.vits.data_dir);
} else {
frontend_ = std::make_unique<Lexicon>(
mgr, config_.model.vits.lexicon, config_.model.vits.tokens,
model_->Punctuations(), model_->Language(), config_.model.debug,
model_->IsPiper());
}
}
void InitFrontend() {
if (model_->IsPiper() && !config_.model.vits.data_dir.empty()) {
frontend_ = std::make_unique<PiperPhonemizeLexicon>(
config_.model.vits.tokens, config_.model.vits.data_dir);
} else {
frontend_ = std::make_unique<Lexicon>(
config_.model.vits.lexicon, config_.model.vits.tokens,
model_->Punctuations(), model_->Language(), config_.model.debug,
model_->IsPiper());
}
}
std::vector<int64_t> AddBlank(const std::vector<int64_t> &x) const {
// we assume the blank ID is 0
std::vector<int64_t> buffer(x.size() * 2 + 1);
int32_t i = 1;
for (auto k : x) {
buffer[i] = k;
i += 2;
}
return buffer;
}
GeneratedAudio Process(const std::vector<std::vector<int64_t>> &tokens,
int32_t sid, float speed) const {
int32_t num_tokens = 0;
for (const auto &k : tokens) {
num_tokens += k.size();
}
std::vector<int64_t> x;
x.reserve(num_tokens);
for (const auto &k : tokens) {
x.insert(x.end(), k.begin(), k.end());
}
auto memory_info =
@@ -147,7 +246,7 @@ class OfflineTtsVitsImpl : public OfflineTtsImpl {
OfflineTtsConfig config_;
std::unique_ptr<OfflineTtsVitsModel> model_;
std::vector<std::unique_ptr<kaldifst::TextNormalizer>> tn_list_;
Lexicon lexicon_;
std::unique_ptr<OfflineTtsFrontend> frontend_;
};
} // namespace sherpa_onnx

51
sherpa-onnx/csrc/offline-tts-vits-model-config.cc
View File

@@ -13,6 +13,9 @@ void OfflineTtsVitsModelConfig::Register(ParseOptions *po) {
po->Register("vits-model", &model, "Path to VITS model");
po->Register("vits-lexicon", &lexicon, "Path to lexicon.txt for VITS models");
po->Register("vits-tokens", &tokens, "Path to tokens.txt for VITS models");
po->Register("vits-data-dir", &data_dir,
"Path to the directory containing dict for espeak-ng. If it is "
"given, --vits-lexicon is ignored.");
po->Register("vits-noise-scale", &noise_scale, "noise_scale for VITS models");
po->Register("vits-noise-scale-w", &noise_scale_w,
"noise_scale_w for VITS models");
@@ -31,16 +34,6 @@ bool OfflineTtsVitsModelConfig::Validate() const {
return false;
}
if (lexicon.empty()) {
SHERPA_ONNX_LOGE("Please provide --vits-lexicon");
return false;
}
if (!FileExists(lexicon)) {
SHERPA_ONNX_LOGE("--vits-lexicon: %s does not exist", lexicon.c_str());
return false;
}
if (tokens.empty()) {
SHERPA_ONNX_LOGE("Please provide --vits-tokens");
return false;
@@ -51,6 +44,43 @@ bool OfflineTtsVitsModelConfig::Validate() const {
return false;
}
if (data_dir.empty()) {
if (lexicon.empty()) {
SHERPA_ONNX_LOGE("Please provide --vits-lexicon");
return false;
}
if (!FileExists(lexicon)) {
SHERPA_ONNX_LOGE("--vits-lexicon: %s does not exist", lexicon.c_str());
return false;
}
} else {
if (!FileExists(data_dir + "/phontab")) {
SHERPA_ONNX_LOGE("%s/phontab does not exist. Skipping test",
data_dir.c_str());
return false;
}
if (!FileExists(data_dir + "/phonindex")) {
SHERPA_ONNX_LOGE("%s/phonindex does not exist. Skipping test",
data_dir.c_str());
return false;
}
if (!FileExists(data_dir + "/phondata")) {
SHERPA_ONNX_LOGE("%s/phondata does not exist. Skipping test",
data_dir.c_str());
return false;
}
if (!FileExists(data_dir + "/intonations")) {
SHERPA_ONNX_LOGE("%s/intonations does not exist. Skipping test",
data_dir.c_str());
return false;
}
}
return true;
}
@@ -61,6 +91,7 @@ std::string OfflineTtsVitsModelConfig::ToString() const {
os << "model=\"" << model << "\", ";
os << "lexicon=\"" << lexicon << "\", ";
os << "tokens=\"" << tokens << "\", ";
os << "data_dir=\"" << data_dir << "\", ";
os << "noise_scale=" << noise_scale << ", ";
os << "noise_scale_w=" << noise_scale_w << ", ";
os << "length_scale=" << length_scale << ")";

6
sherpa-onnx/csrc/offline-tts-vits-model-config.h
View File

@@ -16,6 +16,10 @@ struct OfflineTtsVitsModelConfig {
std::string lexicon;
std::string tokens;
// If data_dir is given, lexicon is ignored
// data_dir is for piper-phonemize, which uses espeak-ng
std::string data_dir;
float noise_scale = 0.667;
float noise_scale_w = 0.8;
float length_scale = 1;
@@ -28,11 +32,13 @@ struct OfflineTtsVitsModelConfig {
OfflineTtsVitsModelConfig(const std::string &model,
const std::string &lexicon,
const std::string &tokens,
const std::string &data_dir,
float noise_scale = 0.667,
float noise_scale_w = 0.8, float length_scale = 1)
: model(model),
lexicon(lexicon),
tokens(tokens),
data_dir(data_dir),
noise_scale(noise_scale),
noise_scale_w(noise_scale_w),
length_scale(length_scale) {}

9
sherpa-onnx/csrc/offline-tts-vits-model.cc
View File

@@ -51,6 +51,7 @@ class OfflineTtsVitsModel::Impl {
std::string Punctuations() const { return punctuations_; }
std::string Language() const { return language_; }
std::string Voice() const { return voice_; }
bool IsPiper() const { return is_piper_; }
int32_t NumSpeakers() const { return num_speakers_; }
@@ -74,10 +75,12 @@ class OfflineTtsVitsModel::Impl {
Ort::AllocatorWithDefaultOptions allocator; // used in the macro below
SHERPA_ONNX_READ_META_DATA(sample_rate_, "sample_rate");
SHERPA_ONNX_READ_META_DATA(add_blank_, "add_blank");
SHERPA_ONNX_READ_META_DATA_WITH_DEFAULT(add_blank_, "add_blank", 0);
SHERPA_ONNX_READ_META_DATA(num_speakers_, "n_speakers");
SHERPA_ONNX_READ_META_DATA_STR(punctuations_, "punctuation");
SHERPA_ONNX_READ_META_DATA_STR_WITH_DEFAULT(punctuations_, "punctuation",
"");
SHERPA_ONNX_READ_META_DATA_STR(language_, "language");
SHERPA_ONNX_READ_META_DATA_STR_WITH_DEFAULT(voice_, "voice", "");
std::string comment;
SHERPA_ONNX_READ_META_DATA_STR(comment, "comment");
@@ -215,6 +218,7 @@ class OfflineTtsVitsModel::Impl {
int32_t num_speakers_;
std::string punctuations_;
std::string language_;
std::string voice_;
bool is_piper_ = false;
};
@@ -244,6 +248,7 @@ std::string OfflineTtsVitsModel::Punctuations() const {
}
std::string OfflineTtsVitsModel::Language() const { return impl_->Language(); }
std::string OfflineTtsVitsModel::Voice() const { return impl_->Voice(); }
bool OfflineTtsVitsModel::IsPiper() const { return impl_->IsPiper(); }

3
sherpa-onnx/csrc/offline-tts-vits-model.h
View File

@@ -46,7 +46,8 @@ class OfflineTtsVitsModel {
bool AddBlank() const;
std::string Punctuations() const;
std::string Language() const;
std::string Language() const; // e.g., Chinese, English, German, etc.
std::string Voice() const; // e.g., en-us, for espeak-ng
bool IsPiper() const;
int32_t NumSpeakers() const;

9
sherpa-onnx/csrc/offline-tts.cc
View File

@@ -21,6 +21,12 @@ void OfflineTtsConfig::Register(ParseOptions *po) {
"Multiple filenames are separated by a comma and they are "
"applied from left to right. An example value: "
"rule1.fst,rule2,fst,rule3.fst");
po->Register(
"tts-max-num-sentences", &max_num_sentences,
"Maximum number of sentences that we process at a time. "
"This is to avoid OOM for very long input text. "
"If you set it to -1, then we process all sentences in a single batch.");
}
bool OfflineTtsConfig::Validate() const {
@@ -43,7 +49,8 @@ std::string OfflineTtsConfig::ToString() const {
os << "OfflineTtsConfig(";
os << "model=" << model.ToString() << ", ";
os << "rule_fsts=\"" << rule_fsts << "\")";
os << "rule_fsts=\"" << rule_fsts << "\", ";
os << "max_num_sentences=" << max_num_sentences << ")";
return os.str();
}

11
sherpa-onnx/csrc/offline-tts.h
View File

@@ -28,10 +28,17 @@ struct OfflineTtsConfig {
// If there are multiple rules, they are applied from left to right.
std::string rule_fsts;
// Maximum number of sentences that we process at a time.
// This is to avoid OOM for very long input text.
// If you set it to -1, then we process all sentences in a single batch.
int32_t max_num_sentences = 2;
OfflineTtsConfig() = default;
OfflineTtsConfig(const OfflineTtsModelConfig &model,
const std::string &rule_fsts)
: model(model), rule_fsts(rule_fsts) {}
const std::string &rule_fsts, int32_t max_num_sentences)
: model(model),
rule_fsts(rule_fsts),
max_num_sentences(max_num_sentences) {}
void Register(ParseOptions *po);
bool Validate() const;

170
sherpa-onnx/csrc/piper-phonemize-lexicon.cc Normal file
View File

@@ -0,0 +1,170 @@
// sherpa-onnx/csrc/piper-phonemize-lexicon.cc
//
// Copyright (c) 2022-2023 Xiaomi Corporation
#include "sherpa-onnx/csrc/piper-phonemize-lexicon.h"
#include <codecvt>
#include <fstream>
#include <locale>
#include <map>
#include <mutex> // NOLINT
#include <sstream>
#include <string>
#include <utility>
#include <vector>
#if __ANDROID_API__ >= 9
#include <strstream>
#include "android/asset_manager.h"
#include "android/asset_manager_jni.h"
#endif
#include "espeak-ng/speak_lib.h"
#include "phoneme_ids.hpp"
#include "phonemize.hpp"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
namespace sherpa_onnx {
static std::unordered_map<char32_t, int32_t> ReadTokens(std::istream &is) {
std::wstring_convert<std::codecvt_utf8<char32_t>, char32_t> conv;
std::unordered_map<char32_t, int32_t> token2id;
std::string line;
std::string sym;
std::u32string s;
int32_t id;
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 when reading tokens: %s", line.c_str());
exit(-1);
}
s = conv.from_bytes(sym);
if (s.size() != 1) {
SHERPA_ONNX_LOGE("Error when reading tokens at Line %s. size: %d",
line.c_str(), static_cast<int32_t>(s.size()));
exit(-1);
}
char32_t c = s[0];
if (token2id.count(c)) {
SHERPA_ONNX_LOGE("Duplicated token %s. Line %s. Existing ID: %d",
sym.c_str(), line.c_str(), token2id.at(c));
exit(-1);
}
token2id.insert({c, id});
}
return token2id;
}
// see the function "phonemes_to_ids" from
// https://github.com/rhasspy/piper/blob/master/notebooks/piper_inference_(ONNX).ipynb
static std::vector<int64_t> PhonemesToIds(
const std::unordered_map<char32_t, int32_t> &token2id,
const std::vector<piper::Phoneme> &phonemes) {
// see
// https://github.com/rhasspy/piper-phonemize/blob/master/src/phoneme_ids.hpp#L17
int32_t pad = token2id.at(U'_');
int32_t bos = token2id.at(U'^');
int32_t eos = token2id.at(U'$');
std::vector<int64_t> ans;
ans.reserve(phonemes.size());
ans.push_back(bos);
for (auto p : phonemes) {
if (token2id.count(p)) {
ans.push_back(token2id.at(p));
ans.push_back(pad);
} else {
SHERPA_ONNX_LOGE("Skip unkown phonemes. Unicode codepoint: \\U+%04x.", p);
}
}
ans.push_back(eos);
return ans;
}
void InitEspeak(const std::string &data_dir) {
static std::once_flag init_flag;
std::call_once(init_flag, [data_dir]() {
int32_t result =
espeak_Initialize(AUDIO_OUTPUT_SYNCHRONOUS, 0, data_dir.c_str(), 0);
if (result != 22050) {
SHERPA_ONNX_LOGE(
"Failed to initialize espeak-ng with data dir: %s. Return code is: "
"%d",
data_dir.c_str(), result);
exit(-1);
}
});
}
PiperPhonemizeLexicon::PiperPhonemizeLexicon(const std::string &tokens,
const std::string &data_dir)
: data_dir_(data_dir) {
{
std::ifstream is(tokens);
token2id_ = ReadTokens(is);
}
InitEspeak(data_dir_);
}
#if __ANDROID_API__ >= 9
PiperPhonemizeLexicon::PiperPhonemizeLexicon(AAssetManager *mgr,
const std::string &tokens,
const std::string &data_dir) {
{
auto buf = ReadFile(mgr, tokens);
std::istrstream is(buf.data(), buf.size());
token2id_ = ReadTokens(is);
}
// We should copy the directory of espeak-ng-data from the asset to
// some internal or external storage and then pass the directory to data_dir.
InitEspeak(data_dir_);
}
#endif
std::vector<std::vector<int64_t>> PiperPhonemizeLexicon::ConvertTextToTokenIds(
const std::string &text, const std::string &voice /*= ""*/) const {
piper::eSpeakPhonemeConfig config;
// ./bin/espeak-ng-bin --path ./install/share/espeak-ng-data/ --voices
// to list available voices
config.voice = voice; // e.g., voice is en-us
std::vector<std::vector<piper::Phoneme>> phonemes;
piper::phonemize_eSpeak(text, config, phonemes);
std::vector<std::vector<int64_t>> ans;
std::vector<int64_t> phoneme_ids;
for (const auto &p : phonemes) {
phoneme_ids = PhonemesToIds(token2id_, p);
ans.push_back(std::move(phoneme_ids));
}
return ans;
}
} // namespace sherpa_onnx

41
sherpa-onnx/csrc/piper-phonemize-lexicon.h Normal file
View File

@@ -0,0 +1,41 @@
// sherpa-onnx/csrc/piper-phonemize-lexicon.h
//
// Copyright (c) 2022-2023 Xiaomi Corporation
#ifndef SHERPA_ONNX_CSRC_PIPER_PHONEMIZE_LEXICON_H_
#define SHERPA_ONNX_CSRC_PIPER_PHONEMIZE_LEXICON_H_
#include <string>
#include <unordered_map>
#include <vector>
#if __ANDROID_API__ >= 9
#include "android/asset_manager.h"
#include "android/asset_manager_jni.h"
#endif
#include "sherpa-onnx/csrc/offline-tts-frontend.h"
namespace sherpa_onnx {
class PiperPhonemizeLexicon : public OfflineTtsFrontend {
public:
PiperPhonemizeLexicon(const std::string &tokens, const std::string &data_dir);
#if __ANDROID_API__ >= 9
PiperPhonemizeLexicon(AAssetManager *mgr, const std::string &tokens,
const std::string &data_dir);
#endif
std::vector<std::vector<int64_t>> ConvertTextToTokenIds(
const std::string &text, const std::string &voice = "") const override;
private:
std::string data_dir_;
// map unicode codepoint to an integer ID
std::unordered_map<char32_t, int32_t> token2id_;
};
} // namespace sherpa_onnx
#endif // SHERPA_ONNX_CSRC_PIPER_PHONEMIZE_LEXICON_H_

10
sherpa-onnx/csrc/piper-phonemize-test.cc
View File

@@ -48,7 +48,7 @@ TEST(PiperPhonemize, Case1) {
piper::eSpeakPhonemeConfig config;
// ./bin/espeak-ng --path ./install/share/espeak-ng-data/ --voices
// ./bin/espeak-ng-bin --path ./install/share/espeak-ng-data/ --voices
// to list available voices
config.voice = "en-us";
@@ -61,15 +61,15 @@ TEST(PiperPhonemize, Case1) {
}
std::cout << "\n";
std::vector<piper::PhonemeId> phonemeIds;
std::map<piper::Phoneme, std::size_t> missingPhonemes;
std::vector<piper::PhonemeId> phoneme_ids;
std::map<piper::Phoneme, std::size_t> missing_phonemes;
{
piper::PhonemeIdConfig config;
phonemes_to_ids(phonemes[0], config, phonemeIds, missingPhonemes);
phonemes_to_ids(phonemes[0], config, phoneme_ids, missing_phonemes);
}
for (int32_t p : phonemeIds) {
for (int32_t p : phoneme_ids) {
std::cout << p << " ";
}
std::cout << "\n";