242 lines
7.7 KiB
C++
242 lines
7.7 KiB
C++
// sherpa-onnx/csrc/online-recognizer.cc
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//
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// Copyright (c) 2023 Xiaomi Corporation
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// Copyright (c) 2023 Pingfeng Luo
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#include "sherpa-onnx/csrc/online-recognizer.h"
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#include <algorithm>
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#include <cassert>
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#include <iomanip>
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#include <memory>
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#include <sstream>
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#include <utility>
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#include <vector>
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#include "sherpa-onnx/csrc/file-utils.h"
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#include "sherpa-onnx/csrc/online-recognizer-impl.h"
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#include "sherpa-onnx/csrc/text-utils.h"
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namespace sherpa_onnx {
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namespace {
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/// Helper for `OnlineRecognizerResult::AsJsonString()`
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template <typename T>
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std::string VecToString(const std::vector<T> &vec, int32_t precision = 6) {
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std::ostringstream oss;
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if (precision != 0) {
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oss << std::fixed << std::setprecision(precision);
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}
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oss << "[";
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std::string sep = "";
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for (const auto &item : vec) {
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oss << sep << item;
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sep = ", ";
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}
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oss << "]";
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return oss.str();
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}
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/// Helper for `OnlineRecognizerResult::AsJsonString()`
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template <> // explicit specialization for T = std::string
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std::string VecToString<std::string>(const std::vector<std::string> &vec,
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int32_t) { // ignore 2nd arg
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std::ostringstream oss;
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oss << "[";
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std::string sep = "";
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for (const auto &item : vec) {
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oss << sep << std::quoted(item);
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sep = ", ";
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}
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oss << "]";
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return oss.str();
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}
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} // namespace
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std::string OnlineRecognizerResult::AsJsonString() const {
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std::ostringstream os;
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os << "{ ";
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os << "\"text\": " << std::quoted(text) << ", ";
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os << "\"tokens\": " << VecToString(tokens) << ", ";
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os << "\"timestamps\": " << VecToString(timestamps, 2) << ", ";
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os << "\"ys_probs\": " << VecToString(ys_probs, 6) << ", ";
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os << "\"lm_probs\": " << VecToString(lm_probs, 6) << ", ";
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os << "\"context_scores\": " << VecToString(context_scores, 6) << ", ";
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os << "\"segment\": " << segment << ", ";
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os << "\"words\": " << VecToString(words, 0) << ", ";
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os << "\"start_time\": " << std::fixed << std::setprecision(2) << start_time
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<< ", ";
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os << "\"is_final\": " << (is_final ? "true" : "false");
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os << "}";
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return os.str();
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}
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void OnlineRecognizerConfig::Register(ParseOptions *po) {
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feat_config.Register(po);
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model_config.Register(po);
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endpoint_config.Register(po);
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lm_config.Register(po);
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ctc_fst_decoder_config.Register(po);
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po->Register("enable-endpoint", &enable_endpoint,
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"True to enable endpoint detection. False to disable it.");
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po->Register("max-active-paths", &max_active_paths,
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"beam size used in modified beam search.");
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po->Register("blank-penalty", &blank_penalty,
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"The penalty applied on blank symbol during decoding. "
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"Note: It is a positive value. "
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"Increasing value will lead to lower deletion at the cost"
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"of higher insertions. "
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"Currently only applicable for transducer models.");
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po->Register("hotwords-score", &hotwords_score,
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"The bonus score for each token in context word/phrase. "
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"Used only when decoding_method is modified_beam_search");
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po->Register(
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"hotwords-file", &hotwords_file,
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"The file containing hotwords, one words/phrases per line, For example: "
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"HELLO WORLD"
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"你好世界");
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po->Register("decoding-method", &decoding_method,
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"decoding method,"
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"now support greedy_search and modified_beam_search.");
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po->Register("temperature-scale", &temperature_scale,
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"Temperature scale for confidence computation in decoding.");
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po->Register(
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"rule-fsts", &rule_fsts,
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"If not empty, it specifies fsts for inverse text normalization. "
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"If there are multiple fsts, they are separated by a comma.");
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po->Register(
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"rule-fars", &rule_fars,
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"If not empty, it specifies fst archives for inverse text normalization. "
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"If there are multiple archives, they are separated by a comma.");
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}
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bool OnlineRecognizerConfig::Validate() const {
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if (decoding_method == "modified_beam_search" && !lm_config.model.empty()) {
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if (max_active_paths <= 0) {
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SHERPA_ONNX_LOGE("max_active_paths is less than 0! Given: %d",
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max_active_paths);
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return false;
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}
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if (!lm_config.Validate()) {
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return false;
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}
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}
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if (!hotwords_file.empty() && decoding_method != "modified_beam_search") {
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SHERPA_ONNX_LOGE(
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"Please use --decoding-method=modified_beam_search if you"
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" provide --hotwords-file. Given --decoding-method=%s",
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decoding_method.c_str());
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return false;
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}
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if (!ctc_fst_decoder_config.graph.empty() &&
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!ctc_fst_decoder_config.Validate()) {
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SHERPA_ONNX_LOGE("Errors in ctc_fst_decoder_config");
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return false;
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}
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if (!hotwords_file.empty() && !FileExists(hotwords_file)) {
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SHERPA_ONNX_LOGE("--hotwords-file: '%s' does not exist",
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hotwords_file.c_str());
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return false;
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}
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if (!rule_fsts.empty()) {
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std::vector<std::string> files;
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SplitStringToVector(rule_fsts, ",", false, &files);
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for (const auto &f : files) {
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if (!FileExists(f)) {
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SHERPA_ONNX_LOGE("Rule fst '%s' does not exist. ", f.c_str());
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return false;
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}
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}
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}
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if (!rule_fars.empty()) {
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std::vector<std::string> files;
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SplitStringToVector(rule_fars, ",", false, &files);
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for (const auto &f : files) {
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if (!FileExists(f)) {
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SHERPA_ONNX_LOGE("Rule far '%s' does not exist. ", f.c_str());
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return false;
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}
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}
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}
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return model_config.Validate();
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}
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std::string OnlineRecognizerConfig::ToString() const {
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std::ostringstream os;
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os << "OnlineRecognizerConfig(";
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os << "feat_config=" << feat_config.ToString() << ", ";
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os << "model_config=" << model_config.ToString() << ", ";
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os << "lm_config=" << lm_config.ToString() << ", ";
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os << "endpoint_config=" << endpoint_config.ToString() << ", ";
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os << "ctc_fst_decoder_config=" << ctc_fst_decoder_config.ToString() << ", ";
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os << "enable_endpoint=" << (enable_endpoint ? "True" : "False") << ", ";
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os << "max_active_paths=" << max_active_paths << ", ";
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os << "hotwords_score=" << hotwords_score << ", ";
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os << "hotwords_file=\"" << hotwords_file << "\", ";
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os << "decoding_method=\"" << decoding_method << "\", ";
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os << "blank_penalty=" << blank_penalty << ", ";
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os << "temperature_scale=" << temperature_scale << ", ";
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os << "rule_fsts=\"" << rule_fsts << "\", ";
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os << "rule_fars=\"" << rule_fars << "\")";
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return os.str();
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}
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OnlineRecognizer::OnlineRecognizer(const OnlineRecognizerConfig &config)
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: impl_(OnlineRecognizerImpl::Create(config)) {}
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#if __ANDROID_API__ >= 9
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OnlineRecognizer::OnlineRecognizer(AAssetManager *mgr,
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const OnlineRecognizerConfig &config)
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: impl_(OnlineRecognizerImpl::Create(mgr, config)) {}
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#endif
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OnlineRecognizer::~OnlineRecognizer() = default;
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std::unique_ptr<OnlineStream> OnlineRecognizer::CreateStream() const {
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return impl_->CreateStream();
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}
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std::unique_ptr<OnlineStream> OnlineRecognizer::CreateStream(
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const std::string &hotwords) const {
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return impl_->CreateStream(hotwords);
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}
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bool OnlineRecognizer::IsReady(OnlineStream *s) const {
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return impl_->IsReady(s);
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}
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void OnlineRecognizer::WarmpUpRecognizer(int32_t warmup, int32_t mbs) const {
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if (warmup > 0) {
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impl_->WarmpUpRecognizer(warmup, mbs);
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}
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}
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void OnlineRecognizer::DecodeStreams(OnlineStream **ss, int32_t n) const {
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impl_->DecodeStreams(ss, n);
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}
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OnlineRecognizerResult OnlineRecognizer::GetResult(OnlineStream *s) const {
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return impl_->GetResult(s);
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}
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bool OnlineRecognizer::IsEndpoint(OnlineStream *s) const {
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return impl_->IsEndpoint(s);
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}
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void OnlineRecognizer::Reset(OnlineStream *s) const { impl_->Reset(s); }
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} // namespace sherpa_onnx
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