Break text into sentences for tts. (#460)

This is for models that are not using piper-phonemize as their front-end.

sherpa-onnx/csrc/lexicon.cc

@@ -88,8 +88,8 @@ static std::vector<int32_t> ConvertTokensToIds(
 
 Lexicon::Lexicon(const std::string &lexicon, const std::string &tokens,
                  const std::string &punctuations, const std::string &language,
-                 bool debug /*= false*/, bool is_piper /*= false*/)
-    : debug_(debug), is_piper_(is_piper) {
+                 bool debug /*= false*/)
+    : debug_(debug) {
   InitLanguage(language);
 
   {
@@ -108,9 +108,9 @@ Lexicon::Lexicon(const std::string &lexicon, const std::string &tokens,
 #if __ANDROID_API__ >= 9
 Lexicon::Lexicon(AAssetManager *mgr, const std::string &lexicon,
                  const std::string &tokens, const std::string &punctuations,
-                 const std::string &language, bool debug /*= false*/,
-                 bool is_piper /*= false*/)
-    : debug_(debug), is_piper_(is_piper) {
+                 const std::string &language, bool debug /*= false*/
+                 )
+    : debug_(debug) {
   InitLanguage(language);
 
   {
@@ -132,16 +132,10 @@ Lexicon::Lexicon(AAssetManager *mgr, const std::string &lexicon,
 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);
-    case Language::kGerman:
-      return ConvertTextToTokenIdsGerman(text);
-    case Language::kSpanish:
-      return ConvertTextToTokenIdsSpanish(text);
-    case Language::kFrench:
-      return ConvertTextToTokenIdsFrench(text);
     case Language::kChinese:
       return ConvertTextToTokenIdsChinese(text);
+    case Language::kNotChinese:
+      return ConvertTextToTokenIdsNotChinese(text);
     default:
       SHERPA_ONNX_LOGE("Unknown language: %d", static_cast<int32_t>(language_));
       exit(-1);
@@ -197,7 +191,8 @@ std::vector<std::vector<int64_t>> Lexicon::ConvertTextToTokenIdsChinese(
     fprintf(stderr, "\n");
   }
 
-  std::vector<int64_t> ans;
+  std::vector<std::vector<int64_t>> ans;
+  std::vector<int64_t> this_sentence;
 
   int32_t blank = -1;
   if (token2id_.count(" ")) {
@@ -212,15 +207,32 @@ std::vector<std::vector<int64_t>> Lexicon::ConvertTextToTokenIdsChinese(
   }
 
   if (sil != -1) {
-    ans.push_back(sil);
+    this_sentence.push_back(sil);
   }
 
   for (const auto &w : words) {
+    if (w == "." || w == ";" || w == "!" || w == "?" || w == "-" || w == ":" ||
+        w == "。" || w == "；" || w == "！" || w == "？" || w == "：" ||
+        w == "”" ||
+        // not sentence break
+        w == "," || w == "“" || w == "，" || w == "、") {
       if (punctuations_.count(w)) {
         if (token2id_.count(w)) {
-        ans.push_back(token2id_.at(w));
+          this_sentence.push_back(token2id_.at(w));
         } else if (sil != -1) {
-        ans.push_back(sil);
+          this_sentence.push_back(sil);
+        }
+      }
+
+      if (w != "," && w != "“" && w != "，" && w != "、") {
+        if (eos != -1) {
+          this_sentence.push_back(eos);
+        }
+        ans.push_back(std::move(this_sentence));
+
+        if (sil != -1) {
+          this_sentence.push_back(sil);
+        }
       }
       continue;
     }
@@ -231,24 +243,26 @@ std::vector<std::vector<int64_t>> Lexicon::ConvertTextToTokenIdsChinese(
     }
 
     const auto &token_ids = word2ids_.at(w);
-    ans.insert(ans.end(), token_ids.begin(), token_ids.end());
+    this_sentence.insert(this_sentence.end(), token_ids.begin(),
+                         token_ids.end());
     if (blank != -1) {
-      ans.push_back(blank);
+      this_sentence.push_back(blank);
     }
   }
 
   if (sil != -1) {
-    ans.push_back(sil);
+    this_sentence.push_back(sil);
   }
 
   if (eos != -1) {
-    ans.push_back(eos);
+    this_sentence.push_back(eos);
   }
+  ans.push_back(std::move(this_sentence));
 
-  return {ans};
+  return ans;
 }
 
-std::vector<std::vector<int64_t>> Lexicon::ConvertTextToTokenIdsEnglish(
+std::vector<std::vector<int64_t>> Lexicon::ConvertTextToTokenIdsNotChinese(
     const std::string &_text) const {
   std::string text(_text);
   ToLowerCase(&text);
@@ -271,14 +285,22 @@ std::vector<std::vector<int64_t>> Lexicon::ConvertTextToTokenIdsEnglish(
 
   int32_t blank = token2id_.at(" ");
 
-  std::vector<int64_t> ans;
-  if (is_piper_ && token2id_.count("^")) {
-    ans.push_back(token2id_.at("^"));  // sos
-  }
+  std::vector<std::vector<int64_t>> ans;
+  std::vector<int64_t> this_sentence;
 
   for (const auto &w : words) {
+    if (w == "." || w == ";" || w == "!" || w == "?" || w == "-" || w == ":" ||
+        // not sentence break
+        w == ",") {
       if (punctuations_.count(w)) {
-      ans.push_back(token2id_.at(w));
+        this_sentence.push_back(token2id_.at(w));
+      }
+
+      if (w != ",") {
+        this_sentence.push_back(blank);
+        ans.push_back(std::move(this_sentence));
+      }
+
       continue;
     }
 
@@ -288,20 +310,21 @@ std::vector<std::vector<int64_t>> Lexicon::ConvertTextToTokenIdsEnglish(
     }
 
     const auto &token_ids = word2ids_.at(w);
-    ans.insert(ans.end(), token_ids.begin(), token_ids.end());
-    ans.push_back(blank);
+    this_sentence.insert(this_sentence.end(), token_ids.begin(),
+                         token_ids.end());
+    this_sentence.push_back(blank);
   }
 
-  if (!ans.empty()) {
+  if (!this_sentence.empty()) {
     // remove the last blank
-    ans.resize(ans.size() - 1);
+    this_sentence.resize(this_sentence.size() - 1);
   }
 
-  if (is_piper_ && token2id_.count("$")) {
-    ans.push_back(token2id_.at("$"));  // eos
+  if (!this_sentence.empty()) {
+    ans.push_back(std::move(this_sentence));
   }
 
-  return {ans};
+  return ans;
 }
 
 void Lexicon::InitTokens(std::istream &is) { token2id_ = ReadTokens(is); }
@@ -309,16 +332,10 @@ void Lexicon::InitTokens(std::istream &is) { token2id_ = ReadTokens(is); }
 void Lexicon::InitLanguage(const std::string &_lang) {
   std::string lang(_lang);
   ToLowerCase(&lang);
-  if (lang == "english") {
-    language_ = Language::kEnglish;
-  } else if (lang == "german") {
-    language_ = Language::kGerman;
-  } else if (lang == "spanish") {
-    language_ = Language::kSpanish;
-  } else if (lang == "french") {
-    language_ = Language::kFrench;
-  } else if (lang == "chinese") {
+  if (lang == "chinese") {
     language_ = Language::kChinese;
+  } else if (!lang.empty()) {
+    language_ = Language::kNotChinese;
   } else {
     SHERPA_ONNX_LOGE("Unknown language: %s", _lang.c_str());
     exit(-1);

sherpa-onnx/csrc/lexicon.h

@@ -29,35 +29,19 @@ class Lexicon : public OfflineTtsFrontend {
   // 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);
+          bool debug = false);
 
 #if __ANDROID_API__ >= 9
   Lexicon(AAssetManager *mgr, const std::string &lexicon,
           const std::string &tokens, const std::string &punctuations,
-          const std::string &language, bool debug = false,
-          bool is_piper = false);
+          const std::string &language, bool debug = false);
 #endif
 
   std::vector<std::vector<int64_t>> ConvertTextToTokenIds(
       const std::string &text, const std::string &voice = "") const override;
 
  private:
-  std::vector<std::vector<int64_t>> ConvertTextToTokenIdsGerman(
-      const std::string &text) const {
-    return ConvertTextToTokenIdsEnglish(text);
-  }
-
-  std::vector<std::vector<int64_t>> ConvertTextToTokenIdsSpanish(
-      const std::string &text) const {
-    return ConvertTextToTokenIdsEnglish(text);
-  }
-
-  std::vector<std::vector<int64_t>> ConvertTextToTokenIdsFrench(
-      const std::string &text) const {
-    return ConvertTextToTokenIdsEnglish(text);
-  }
-
-  std::vector<std::vector<int64_t>> ConvertTextToTokenIdsEnglish(
+  std::vector<std::vector<int64_t>> ConvertTextToTokenIdsNotChinese(
       const std::string &text) const;
 
   std::vector<std::vector<int64_t>> ConvertTextToTokenIdsChinese(
@@ -70,10 +54,7 @@ class Lexicon : public OfflineTtsFrontend {
 
  private:
   enum class Language {
-    kEnglish,
-    kGerman,
-    kSpanish,
-    kFrench,
+    kNotChinese,
     kChinese,
     kUnknown,
   };
@@ -84,7 +65,6 @@ class Lexicon : public OfflineTtsFrontend {
   std::unordered_map<std::string, int32_t> token2id_;
   Language language_;
   bool debug_;
-  bool is_piper_;
 
   // for Chinese polyphones
   std::unique_ptr<std::regex> pattern_;

sherpa-onnx/csrc/offline-tts-vits-impl.h

@@ -195,8 +195,7 @@ class OfflineTtsVitsImpl : public OfflineTtsImpl {
     } else {
       frontend_ = std::make_unique<Lexicon>(
           mgr, config_.model.vits.lexicon, config_.model.vits.tokens,
-          model_->Punctuations(), model_->Language(), config_.model.debug,
-          model_->IsPiper());
+          model_->Punctuations(), model_->Language(), config_.model.debug);
     }
   }
 #endif
@@ -208,8 +207,7 @@ class OfflineTtsVitsImpl : public OfflineTtsImpl {
     } else {
       frontend_ = std::make_unique<Lexicon>(
           config_.model.vits.lexicon, config_.model.vits.tokens,
-          model_->Punctuations(), model_->Language(), config_.model.debug,
-          model_->IsPiper());
+          model_->Punctuations(), model_->Language(), config_.model.debug);
     }
   }