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Add HLG decoding for streaming CTC models (#731)

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This commit is contained in:
Fangjun Kuang
2024-04-03 21:31:42 +08:00
committed by GitHub
parent f8832cb5f2
commit db67e00c77
28 changed files with 668 additions and 82 deletions
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1
sherpa-onnx/python/csrc/CMakeLists.txt
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@@ -18,6 +18,7 @@ set(srcs
offline-wenet-ctc-model-config.cc
offline-whisper-model-config.cc
offline-zipformer-ctc-model-config.cc
online-ctc-fst-decoder-config.cc
online-lm-config.cc
online-model-config.cc
online-paraformer-model-config.cc

23
sherpa-onnx/python/csrc/online-ctc-fst-decoder-config.cc Normal file
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@@ -0,0 +1,23 @@
// sherpa-onnx/python/csrc/online-ctc-fst-decoder-config.cc
//
// Copyright (c) 2024 Xiaomi Corporation
#include "sherpa-onnx/python/csrc/online-ctc-fst-decoder-config.h"
#include <string>
#include "sherpa-onnx/csrc/online-ctc-fst-decoder-config.h"
namespace sherpa_onnx {
void PybindOnlineCtcFstDecoderConfig(py::module *m) {
using PyClass = OnlineCtcFstDecoderConfig;
py::class_<PyClass>(*m, "OnlineCtcFstDecoderConfig")
.def(py::init<const std::string &, int32_t>(), py::arg("graph") = "",
py::arg("max_active") = 3000)
.def_readwrite("graph", &PyClass::graph)
.def_readwrite("max_active", &PyClass::max_active)
.def("__str__", &PyClass::ToString);
}
} // namespace sherpa_onnx

16
sherpa-onnx/python/csrc/online-ctc-fst-decoder-config.h Normal file
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@@ -0,0 +1,16 @@
// sherpa-onnx/python/csrc/online-ctc-fst-decoder-config.h
//
// Copyright (c) 2024 Xiaomi Corporation
#ifndef SHERPA_ONNX_PYTHON_CSRC_ONLINE_CTC_FST_DECODER_CONFIG_H_
#define SHERPA_ONNX_PYTHON_CSRC_ONLINE_CTC_FST_DECODER_CONFIG_H_
#include "sherpa-onnx/python/csrc/sherpa-onnx.h"
namespace sherpa_onnx {
void PybindOnlineCtcFstDecoderConfig(py::module *m);
}
#endif // SHERPA_ONNX_PYTHON_CSRC_ONLINE_CTC_FST_DECODER_CONFIG_H_

42
sherpa-onnx/python/csrc/online-recognizer.cc
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@@ -24,8 +24,7 @@ static void PybindOnlineRecognizerResult(py::module *m) {
"tokens",
[](PyClass &self) -> std::vector<std::string> { return self.tokens; })
.def_property_readonly(
"start_time",
[](PyClass &self) -> float { return self.start_time; })
"start_time", [](PyClass &self) -> float { return self.start_time; })
.def_property_readonly(
"timestamps",
[](PyClass &self) -> std::vector<float> { return self.timestamps; })
@@ -35,37 +34,38 @@ static void PybindOnlineRecognizerResult(py::module *m) {
.def_property_readonly(
"lm_probs",
[](PyClass &self) -> std::vector<float> { return self.lm_probs; })
.def_property_readonly("context_scores",
[](PyClass &self) -> std::vector<float> {
return self.context_scores;
})
.def_property_readonly(
"context_scores",
[](PyClass &self) -> std::vector<float> {
return self.context_scores;
})
"segment", [](PyClass &self) -> int32_t { return self.segment; })
.def_property_readonly(
"segment",
[](PyClass &self) -> int32_t { return self.segment; })
.def_property_readonly(
"is_final",
[](PyClass &self) -> bool { return self.is_final; })
"is_final", [](PyClass &self) -> bool { return self.is_final; })
.def("as_json_string", &PyClass::AsJsonString,
py::call_guard<py::gil_scoped_release>());
py::call_guard<py::gil_scoped_release>());
}
static void PybindOnlineRecognizerConfig(py::module *m) {
using PyClass = OnlineRecognizerConfig;
py::class_<PyClass>(*m, "OnlineRecognizerConfig")
.def(py::init<const FeatureExtractorConfig &, const OnlineModelConfig &,
const OnlineLMConfig &, const EndpointConfig &, bool,
const std::string &, int32_t, const std::string &, float,
float>(),
py::arg("feat_config"), py::arg("model_config"),
py::arg("lm_config") = OnlineLMConfig(), py::arg("endpoint_config"),
py::arg("enable_endpoint"), py::arg("decoding_method"),
py::arg("max_active_paths") = 4, py::arg("hotwords_file") = "",
py::arg("hotwords_score") = 0, py::arg("blank_penalty") = 0.0)
.def(
py::init<const FeatureExtractorConfig &, const OnlineModelConfig &,
const OnlineLMConfig &, const EndpointConfig &,
const OnlineCtcFstDecoderConfig &, bool, const std::string &,
int32_t, const std::string &, float, float>(),
py::arg("feat_config"), py::arg("model_config"),
py::arg("lm_config") = OnlineLMConfig(),
py::arg("endpoint_config") = EndpointConfig(),
py::arg("ctc_fst_decoder_config") = OnlineCtcFstDecoderConfig(),
py::arg("enable_endpoint"), py::arg("decoding_method"),
py::arg("max_active_paths") = 4, py::arg("hotwords_file") = "",
py::arg("hotwords_score") = 0, py::arg("blank_penalty") = 0.0)
.def_readwrite("feat_config", &PyClass::feat_config)
.def_readwrite("model_config", &PyClass::model_config)
.def_readwrite("lm_config", &PyClass::lm_config)
.def_readwrite("endpoint_config", &PyClass::endpoint_config)
.def_readwrite("ctc_fst_decoder_config", &PyClass::ctc_fst_decoder_config)
.def_readwrite("enable_endpoint", &PyClass::enable_endpoint)
.def_readwrite("decoding_method", &PyClass::decoding_method)
.def_readwrite("max_active_paths", &PyClass::max_active_paths)

2
sherpa-onnx/python/csrc/sherpa-onnx.cc
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@@ -15,6 +15,7 @@
#include "sherpa-onnx/python/csrc/offline-model-config.h"
#include "sherpa-onnx/python/csrc/offline-recognizer.h"
#include "sherpa-onnx/python/csrc/offline-stream.h"
#include "sherpa-onnx/python/csrc/online-ctc-fst-decoder-config.h"
#include "sherpa-onnx/python/csrc/online-lm-config.h"
#include "sherpa-onnx/python/csrc/online-model-config.h"
#include "sherpa-onnx/python/csrc/online-recognizer.h"
@@ -36,6 +37,7 @@ PYBIND11_MODULE(_sherpa_onnx, m) {
m.doc() = "pybind11 binding of sherpa-onnx";
PybindFeatures(&m);
PybindOnlineCtcFstDecoderConfig(&m);
PybindOnlineModelConfig(&m);
PybindOnlineLMConfig(&m);
PybindOnlineStream(&m);