80060c276d
Please see https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-ctc/nemo/index.html for a list of pre-trained CTC models from NeMo.
60 lines
2.0 KiB
C++
60 lines
2.0 KiB
C++
// sherpa-onnx/python/csrc/offline-stream.cc
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//
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// Copyright (c) 2023 by manyeyes
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#include "sherpa-onnx/python/csrc/offline-stream.h"
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#include "sherpa-onnx/csrc/offline-stream.h"
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namespace sherpa_onnx {
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constexpr const char *kAcceptWaveformUsage = R"(
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Process audio samples.
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Args:
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sample_rate:
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Sample rate of the input samples. If it is different from the one
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expected by the model, we will do resampling inside.
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waveform:
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A 1-D float32 tensor containing audio samples. It must be normalized
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to the range [-1, 1].
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)";
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static void PybindOfflineRecognitionResult(py::module *m) { // NOLINT
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using PyClass = OfflineRecognitionResult;
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py::class_<PyClass>(*m, "OfflineRecognitionResult")
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.def_property_readonly("text",
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[](const PyClass &self) { return self.text; })
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.def_property_readonly("tokens",
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[](const PyClass &self) { return self.tokens; })
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.def_property_readonly(
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"timestamps", [](const PyClass &self) { return self.timestamps; });
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}
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static void PybindOfflineFeatureExtractorConfig(py::module *m) {
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using PyClass = OfflineFeatureExtractorConfig;
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py::class_<PyClass>(*m, "OfflineFeatureExtractorConfig")
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.def(py::init<int32_t, int32_t>(), py::arg("sampling_rate") = 16000,
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py::arg("feature_dim") = 80)
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.def_readwrite("sampling_rate", &PyClass::sampling_rate)
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.def_readwrite("feature_dim", &PyClass::feature_dim)
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.def("__str__", &PyClass::ToString);
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}
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void PybindOfflineStream(py::module *m) {
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PybindOfflineFeatureExtractorConfig(m);
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PybindOfflineRecognitionResult(m);
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using PyClass = OfflineStream;
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py::class_<PyClass>(*m, "OfflineStream")
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.def(
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"accept_waveform",
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[](PyClass &self, float sample_rate, py::array_t<float> waveform) {
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self.AcceptWaveform(sample_rate, waveform.data(), waveform.size());
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},
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py::arg("sample_rate"), py::arg("waveform"), kAcceptWaveformUsage)
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.def_property_readonly("result", &PyClass::GetResult);
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}
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} // namespace sherpa_onnx
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