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Refactor hotwords，support loading hotwords from file (#296)

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This commit is contained in:
Wei Kang
2023-09-14 19:33:17 +08:00
committed by GitHub
parent 087367d7fe
commit 47184f9db7
34 changed files with 803 additions and 300 deletions
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15
sherpa-onnx/python/csrc/offline-recognizer.cc
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@@ -16,17 +16,19 @@ static void PybindOfflineRecognizerConfig(py::module *m) {
py::class_<PyClass>(*m, "OfflineRecognizerConfig")
.def(py::init<const OfflineFeatureExtractorConfig &,
const OfflineModelConfig &, const OfflineLMConfig &,
const std::string &, int32_t, float>(),
const std::string &, int32_t, const std::string &, float>(),
py::arg("feat_config"), py::arg("model_config"),
py::arg("lm_config") = OfflineLMConfig(),
py::arg("decoding_method") = "greedy_search",
py::arg("max_active_paths") = 4, py::arg("context_score") = 1.5)
py::arg("max_active_paths") = 4, py::arg("hotwords_file") = "",
py::arg("hotwords_score") = 1.5)
.def_readwrite("feat_config", &PyClass::feat_config)
.def_readwrite("model_config", &PyClass::model_config)
.def_readwrite("lm_config", &PyClass::lm_config)
.def_readwrite("decoding_method", &PyClass::decoding_method)
.def_readwrite("max_active_paths", &PyClass::max_active_paths)
.def_readwrite("context_score", &PyClass::context_score)
.def_readwrite("hotwords_file", &PyClass::hotwords_file)
.def_readwrite("hotwords_score", &PyClass::hotwords_score)
.def("__str__", &PyClass::ToString);
}
@@ -40,11 +42,10 @@ void PybindOfflineRecognizer(py::module *m) {
[](const PyClass &self) { return self.CreateStream(); })
.def(
"create_stream",
[](PyClass &self,
const std::vector<std::vector<int32_t>> &contexts_list) {
return self.CreateStream(contexts_list);
[](PyClass &self, const std::string &hotwords) {
return self.CreateStream(hotwords);
},
py::arg("contexts_list"))
py::arg("hotwords"))
.def("decode_stream", &PyClass::DecodeStream)
.def("decode_streams",
[](const PyClass &self, std::vector<OfflineStream *> ss) {

4
sherpa-onnx/python/csrc/online-model-config.cc
View File

@@ -21,8 +21,8 @@ void PybindOnlineModelConfig(py::module *m) {
using PyClass = OnlineModelConfig;
py::class_<PyClass>(*m, "OnlineModelConfig")
.def(py::init<const OnlineTransducerModelConfig &,
const OnlineParaformerModelConfig &, std::string &, int32_t,
bool, const std::string &, const std::string &>(),
const OnlineParaformerModelConfig &, const std::string &,
int32_t, bool, const std::string &, const std::string &>(),
py::arg("transducer") = OnlineTransducerModelConfig(),
py::arg("paraformer") = OnlineParaformerModelConfig(),
py::arg("tokens"), py::arg("num_threads"), py::arg("debug") = false,

15
sherpa-onnx/python/csrc/online-recognizer.cc
View File

@@ -29,18 +29,20 @@ static void PybindOnlineRecognizerConfig(py::module *m) {
py::class_<PyClass>(*m, "OnlineRecognizerConfig")
.def(py::init<const FeatureExtractorConfig &, const OnlineModelConfig &,
const OnlineLMConfig &, const EndpointConfig &, bool,
const std::string &, int32_t, float>(),
const std::string &, int32_t, const std::string &, 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("context_score") = 0)
py::arg("max_active_paths") = 4, py::arg("hotwords_file") = "",
py::arg("hotwords_score") = 0)
.def_readwrite("feat_config", &PyClass::feat_config)
.def_readwrite("model_config", &PyClass::model_config)
.def_readwrite("endpoint_config", &PyClass::endpoint_config)
.def_readwrite("enable_endpoint", &PyClass::enable_endpoint)
.def_readwrite("decoding_method", &PyClass::decoding_method)
.def_readwrite("max_active_paths", &PyClass::max_active_paths)
.def_readwrite("context_score", &PyClass::context_score)
.def_readwrite("hotwords_file", &PyClass::hotwords_file)
.def_readwrite("hotwords_score", &PyClass::hotwords_score)
.def("__str__", &PyClass::ToString);
}
@@ -55,11 +57,10 @@ void PybindOnlineRecognizer(py::module *m) {
[](const PyClass &self) { return self.CreateStream(); })
.def(
"create_stream",
[](PyClass &self,
const std::vector<std::vector<int32_t>> &contexts_list) {
return self.CreateStream(contexts_list);
[](PyClass &self, const std::string &hotwords) {
return self.CreateStream(hotwords);
},
py::arg("contexts_list"))
py::arg("hotwords"))
.def("is_ready", &PyClass::IsReady)
.def("decode_stream", &PyClass::DecodeStream)
.def("decode_streams",