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https://github.com/k2-fsa/sherpa-onnx.git
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c691318b95
This PR adds RK NPU support for SenseVoice non-streaming ASR models by implementing a new RKNN backend with greedy CTC decoding. - Adds offline RKNN implementation for SenseVoice models including model loading, feature processing, and CTC decoding - Introduces export tools to convert SenseVoice models from PyTorch to ONNX and then to RKNN format - Implements provider-aware validation to prevent mismatched model and provider usage
29 lines
767 B
C++
29 lines
767 B
C++
// sherpa-onnx/csrc/rknn/offline-ctc-greedy-search-decoder-rknn.h
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//
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// Copyright (c) 2025 Xiaomi Corporation
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#ifndef SHERPA_ONNX_CSRC_RKNN_OFFLINE_CTC_GREEDY_SEARCH_DECODER_RKNN_H_
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#define SHERPA_ONNX_CSRC_RKNN_OFFLINE_CTC_GREEDY_SEARCH_DECODER_RKNN_H_
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#include <vector>
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#include "sherpa-onnx/csrc/offline-ctc-decoder.h"
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namespace sherpa_onnx {
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class OfflineCtcGreedySearchDecoderRknn {
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public:
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explicit OfflineCtcGreedySearchDecoderRknn(int32_t blank_id)
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: blank_id_(blank_id) {}
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OfflineCtcDecoderResult Decode(const float *logits, int32_t num_frames,
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int32_t vocab_size);
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private:
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int32_t blank_id_;
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};
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} // namespace sherpa_onnx
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#endif // SHERPA_ONNX_CSRC_RKNN_OFFLINE_CTC_GREEDY_SEARCH_DECODER_RKNN_H_
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