online-recognizer.cc
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// sherpa-onnx/csrc/online-recognizer.cc
//
// Copyright (c) 2023 Xiaomi Corporation
#include "sherpa-onnx/csrc/online-recognizer.h"
#include <assert.h>
#include <memory>
#include <sstream>
#include <utility>
#include <vector>
#include "sherpa-onnx/csrc/online-transducer-decoder.h"
#include "sherpa-onnx/csrc/online-transducer-greedy-search-decoder.h"
#include "sherpa-onnx/csrc/online-transducer-model.h"
#include "sherpa-onnx/csrc/symbol-table.h"
namespace sherpa_onnx {
static OnlineRecognizerResult Convert(const OnlineTransducerDecoderResult &src,
const SymbolTable &sym_table) {
std::string text;
for (auto t : src.tokens) {
text += sym_table[t];
}
OnlineRecognizerResult ans;
ans.text = std::move(text);
return ans;
}
std::string OnlineRecognizerConfig::ToString() const {
std::ostringstream os;
os << "OnlineRecognizerConfig(";
os << "feat_config=" << feat_config.ToString() << ", ";
os << "model_config=" << model_config.ToString() << ", ";
os << "tokens=\"" << tokens << "\")";
return os.str();
}
class OnlineRecognizer::Impl {
public:
explicit Impl(const OnlineRecognizerConfig &config)
: config_(config),
model_(OnlineTransducerModel::Create(config.model_config)),
sym_(config.tokens) {
decoder_ =
std::make_unique<OnlineTransducerGreedySearchDecoder>(model_.get());
}
std::unique_ptr<OnlineStream> CreateStream() const {
auto stream = std::make_unique<OnlineStream>(config_.feat_config);
stream->SetResult(decoder_->GetEmptyResult());
stream->SetStates(model_->GetEncoderInitStates());
return stream;
}
bool IsReady(OnlineStream *s) const {
return s->GetNumProcessedFrames() + model_->ChunkSize() <
s->NumFramesReady();
}
void DecodeStreams(OnlineStream **ss, int32_t n) {
if (n != 1) {
fprintf(stderr, "only n == 1 is implemented\n");
exit(-1);
}
OnlineStream *s = ss[0];
assert(IsReady(s));
int32_t chunk_size = model_->ChunkSize();
int32_t chunk_shift = model_->ChunkShift();
int32_t feature_dim = s->FeatureDim();
std::array<int64_t, 3> x_shape{1, chunk_size, feature_dim};
auto memory_info =
Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
std::vector<float> features =
s->GetFrames(s->GetNumProcessedFrames(), chunk_size);
s->GetNumProcessedFrames() += chunk_shift;
Ort::Value x =
Ort::Value::CreateTensor(memory_info, features.data(), features.size(),
x_shape.data(), x_shape.size());
auto pair = model_->RunEncoder(std::move(x), s->GetStates());
s->SetStates(std::move(pair.second));
std::vector<OnlineTransducerDecoderResult> results = {s->GetResult()};
decoder_->Decode(std::move(pair.first), &results);
s->SetResult(results[0]);
}
OnlineRecognizerResult GetResult(OnlineStream *s) {
OnlineTransducerDecoderResult decoder_result = s->GetResult();
decoder_->StripLeadingBlanks(&decoder_result);
return Convert(decoder_result, sym_);
}
private:
OnlineRecognizerConfig config_;
std::unique_ptr<OnlineTransducerModel> model_;
std::unique_ptr<OnlineTransducerDecoder> decoder_;
SymbolTable sym_;
};
OnlineRecognizer::OnlineRecognizer(const OnlineRecognizerConfig &config)
: impl_(std::make_unique<Impl>(config)) {}
OnlineRecognizer::~OnlineRecognizer() = default;
std::unique_ptr<OnlineStream> OnlineRecognizer::CreateStream() const {
return impl_->CreateStream();
}
bool OnlineRecognizer::IsReady(OnlineStream *s) const {
return impl_->IsReady(s);
}
void OnlineRecognizer::DecodeStreams(OnlineStream **ss, int32_t n) {
impl_->DecodeStreams(ss, n);
}
OnlineRecognizerResult OnlineRecognizer::GetResult(OnlineStream *s) {
return impl_->GetResult(s);
}
} // namespace sherpa_onnx