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.
43 lines
1.2 KiB
C++
43 lines
1.2 KiB
C++
// sherpa-onnx/csrc/offline-ctc-decoder.h
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//
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// Copyright (c) 2023 Xiaomi Corporation
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#ifndef SHERPA_ONNX_CSRC_OFFLINE_CTC_DECODER_H_
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#define SHERPA_ONNX_CSRC_OFFLINE_CTC_DECODER_H_
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#include <vector>
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#include "onnxruntime_cxx_api.h" // NOLINT
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namespace sherpa_onnx {
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struct OfflineCtcDecoderResult {
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/// The decoded token IDs
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std::vector<int64_t> tokens;
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/// timestamps[i] contains the output frame index where tokens[i] is decoded.
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/// Note: The index is after subsampling
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std::vector<int32_t> timestamps;
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};
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class OfflineCtcDecoder {
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public:
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virtual ~OfflineCtcDecoder() = default;
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/** Run CTC decoding given the output from the encoder model.
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*
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* @param log_probs A 3-D tensor of shape (N, T, vocab_size) containing
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* lob_probs.
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* @param log_probs_length A 1-D tensor of shape (N,) containing number
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* of valid frames in log_probs before padding.
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*
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* @return Return a vector of size `N` containing the decoded results.
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*/
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virtual std::vector<OfflineCtcDecoderResult> Decode(
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Ort::Value log_probs, Ort::Value log_probs_length) = 0;
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};
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} // namespace sherpa_onnx
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#endif // SHERPA_ONNX_CSRC_OFFLINE_CTC_DECODER_H_
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