offline-ctc-decoder.h
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// sherpa-onnx/csrc/offline-ctc-decoder.h
//
// Copyright (c) 2023 Xiaomi Corporation
#ifndef SHERPA_ONNX_CSRC_OFFLINE_CTC_DECODER_H_
#define SHERPA_ONNX_CSRC_OFFLINE_CTC_DECODER_H_
#include <vector>
#include "onnxruntime_cxx_api.h" // NOLINT
namespace sherpa_onnx {
struct OfflineCtcDecoderResult {
/// The decoded token IDs
std::vector<int64_t> tokens;
/// The decoded word IDs
/// Note: tokens.size() is usually not equal to words.size()
/// words is empty for greedy search decoding.
/// it is not empty when an HLG graph or an HLG graph is used.
std::vector<int32_t> words;
/// timestamps[i] contains the output frame index where tokens[i] is decoded.
/// Note: The index is after subsampling
///
/// tokens.size() == timestamps.size()
std::vector<int32_t> timestamps;
};
class OfflineCtcDecoder {
public:
virtual ~OfflineCtcDecoder() = default;
/** Run CTC decoding given the output from the encoder model.
*
* @param log_probs A 3-D tensor of shape (N, T, vocab_size) containing
* lob_probs.
* @param log_probs_length A 1-D tensor of shape (N,) containing number
* of valid frames in log_probs before padding.
*
* @return Return a vector of size `N` containing the decoded results.
*/
virtual std::vector<OfflineCtcDecoderResult> Decode(
Ort::Value log_probs, Ort::Value log_probs_length) = 0;
};
} // namespace sherpa_onnx
#endif // SHERPA_ONNX_CSRC_OFFLINE_CTC_DECODER_H_