277 lines
7.8 KiB
C++
277 lines
7.8 KiB
C++
// sherpa-onnx/csrc/melo-tts-lexicon.cc
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//
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// Copyright (c) 2022-2024 Xiaomi Corporation
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#include "sherpa-onnx/csrc/melo-tts-lexicon.h"
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#include <fstream>
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#include <regex> // NOLINT
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#include <utility>
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#include "cppjieba/Jieba.hpp"
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#include "sherpa-onnx/csrc/file-utils.h"
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#include "sherpa-onnx/csrc/lexicon.h"
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#include "sherpa-onnx/csrc/macros.h"
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#include "sherpa-onnx/csrc/text-utils.h"
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namespace sherpa_onnx {
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class MeloTtsLexicon::Impl {
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public:
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Impl(const std::string &lexicon, const std::string &tokens,
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const std::string &dict_dir,
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const OfflineTtsVitsModelMetaData &meta_data, bool debug)
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: meta_data_(meta_data), debug_(debug) {
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std::string dict = dict_dir + "/jieba.dict.utf8";
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std::string hmm = dict_dir + "/hmm_model.utf8";
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std::string user_dict = dict_dir + "/user.dict.utf8";
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std::string idf = dict_dir + "/idf.utf8";
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std::string stop_word = dict_dir + "/stop_words.utf8";
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AssertFileExists(dict);
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AssertFileExists(hmm);
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AssertFileExists(user_dict);
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AssertFileExists(idf);
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AssertFileExists(stop_word);
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jieba_ =
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std::make_unique<cppjieba::Jieba>(dict, hmm, user_dict, idf, stop_word);
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{
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std::ifstream is(tokens);
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InitTokens(is);
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}
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{
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std::ifstream is(lexicon);
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InitLexicon(is);
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}
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}
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std::vector<TokenIDs> ConvertTextToTokenIds(const std::string &_text) const {
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std::string text = ToLowerCase(_text);
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// see
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// https://github.com/Plachtaa/VITS-fast-fine-tuning/blob/main/text/mandarin.py#L244
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std::regex punct_re{"：|、|；"};
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std::string s = std::regex_replace(text, punct_re, ",");
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std::regex punct_re2("。");
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s = std::regex_replace(s, punct_re2, ".");
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std::regex punct_re3("？");
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s = std::regex_replace(s, punct_re3, "?");
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std::regex punct_re4("！");
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s = std::regex_replace(s, punct_re4, "!");
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std::vector<std::string> words;
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bool is_hmm = true;
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jieba_->Cut(text, words, is_hmm);
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if (debug_) {
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SHERPA_ONNX_LOGE("input text: %s", text.c_str());
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SHERPA_ONNX_LOGE("after replacing punctuations: %s", s.c_str());
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std::ostringstream os;
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std::string sep = "";
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for (const auto &w : words) {
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os << sep << w;
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sep = "_";
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}
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SHERPA_ONNX_LOGE("after jieba processing: %s", os.str().c_str());
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}
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std::vector<TokenIDs> ans;
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TokenIDs this_sentence;
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for (const auto &w : words) {
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auto ids = ConvertWordToIds(w);
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if (ids.tokens.empty()) {
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SHERPA_ONNX_LOGE("Ignore OOV '%s'", w.c_str());
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continue;
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}
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this_sentence.tokens.insert(this_sentence.tokens.end(),
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ids.tokens.begin(), ids.tokens.end());
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this_sentence.tones.insert(this_sentence.tones.end(), ids.tones.begin(),
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ids.tones.end());
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if (w == "." || w == "!" || w == "?" || w == "," || w == "。" ||
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w == "！" || w == "？" || w == "，") {
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ans.push_back(std::move(this_sentence));
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this_sentence = {};
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}
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} // for (const auto &w : words)
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if (!this_sentence.tokens.empty()) {
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ans.push_back(std::move(this_sentence));
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}
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return ans;
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}
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private:
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TokenIDs ConvertWordToIds(const std::string &w) const {
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if (word2ids_.count(w)) {
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return word2ids_.at(w);
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}
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if (token2id_.count(w)) {
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return {{token2id_.at(w)}, {0}};
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}
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TokenIDs ans;
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std::vector<std::string> words = SplitUtf8(w);
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for (const auto &word : words) {
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if (word2ids_.count(word)) {
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auto ids = ConvertWordToIds(word);
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ans.tokens.insert(ans.tokens.end(), ids.tokens.begin(),
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ids.tokens.end());
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ans.tones.insert(ans.tones.end(), ids.tones.begin(), ids.tones.end());
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} else {
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// If the lexicon does not contain the word, we split the word into
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// characters.
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//
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// For instance, if the word is TTS and it is does not exist
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// in the lexicon, we split it into 3 characters: T T S
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std::string s;
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for (char c : word) {
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s = c;
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if (word2ids_.count(s)) {
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const auto &t = word2ids_.at(s);
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ans.tokens.insert(ans.tokens.end(), t.tokens.begin(),
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t.tokens.end());
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ans.tones.insert(ans.tones.end(), t.tones.begin(), t.tones.end());
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}
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}
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}
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}
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return ans;
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}
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void InitTokens(std::istream &is) {
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token2id_ = ReadTokens(is);
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token2id_[" "] = token2id_["_"];
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std::vector<std::pair<std::string, std::string>> puncts = {
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{",", "，"}, {".", "。"}, {"!", "！"}, {"?", "？"}};
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for (const auto &p : puncts) {
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if (token2id_.count(p.first) && !token2id_.count(p.second)) {
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token2id_[p.second] = token2id_[p.first];
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}
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if (!token2id_.count(p.first) && token2id_.count(p.second)) {
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token2id_[p.first] = token2id_[p.second];
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}
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}
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if (!token2id_.count("、") && token2id_.count("，")) {
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token2id_["、"] = token2id_["，"];
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}
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}
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void InitLexicon(std::istream &is) {
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std::string word;
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std::vector<std::string> token_list;
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std::vector<std::string> phone_list;
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std::vector<int64_t> tone_list;
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std::string line;
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std::string phone;
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int32_t line_num = 0;
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while (std::getline(is, line)) {
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++line_num;
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std::istringstream iss(line);
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token_list.clear();
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phone_list.clear();
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tone_list.clear();
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iss >> word;
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ToLowerCase(&word);
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if (word2ids_.count(word)) {
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SHERPA_ONNX_LOGE("Duplicated word: %s at line %d:%s. Ignore it.",
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word.c_str(), line_num, line.c_str());
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continue;
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}
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while (iss >> phone) {
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token_list.push_back(std::move(phone));
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}
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if ((token_list.size() & 1) != 0) {
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SHERPA_ONNX_LOGE("Invalid line %d: '%s'", line_num, line.c_str());
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exit(-1);
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}
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int32_t num_phones = token_list.size() / 2;
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phone_list.reserve(num_phones);
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tone_list.reserve(num_phones);
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for (int32_t i = 0; i != num_phones; ++i) {
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phone_list.push_back(std::move(token_list[i]));
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tone_list.push_back(std::stoi(token_list[i + num_phones], nullptr));
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if (tone_list.back() < 0 || tone_list.back() > 50) {
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SHERPA_ONNX_LOGE("Invalid line %d: '%s'", line_num, line.c_str());
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exit(-1);
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}
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}
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std::vector<int32_t> ids = ConvertTokensToIds(token2id_, phone_list);
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if (ids.empty()) {
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continue;
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}
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if (ids.size() != num_phones) {
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SHERPA_ONNX_LOGE("Invalid line %d: '%s'", line_num, line.c_str());
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exit(-1);
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}
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std::vector<int64_t> ids64{ids.begin(), ids.end()};
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word2ids_.insert(
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{std::move(word), TokenIDs{std::move(ids64), std::move(tone_list)}});
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}
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word2ids_["呣"] = word2ids_["母"];
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word2ids_["嗯"] = word2ids_["恩"];
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}
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private:
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// lexicon.txt is saved in word2ids_
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std::unordered_map<std::string, TokenIDs> word2ids_;
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// tokens.txt is saved in token2id_
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std::unordered_map<std::string, int32_t> token2id_;
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OfflineTtsVitsModelMetaData meta_data_;
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std::unique_ptr<cppjieba::Jieba> jieba_;
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bool debug_ = false;
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};
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MeloTtsLexicon::~MeloTtsLexicon() = default;
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MeloTtsLexicon::MeloTtsLexicon(const std::string &lexicon,
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const std::string &tokens,
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const std::string &dict_dir,
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const OfflineTtsVitsModelMetaData &meta_data,
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bool debug)
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: impl_(std::make_unique<Impl>(lexicon, tokens, dict_dir, meta_data,
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debug)) {}
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std::vector<TokenIDs> MeloTtsLexicon::ConvertTextToTokenIds(
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const std::string &text, const std::string & /*unused_voice = ""*/) const {
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return impl_->ConvertTextToTokenIds(text);
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}
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} // namespace sherpa_onnx
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