espnet.nets.beam_search.beam_search

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espnet.nets.beam_search.beam_search(x: Tensor, sos: int, eos: int, beam_size: int, vocab_size: int, scorers: Dict[str, ScorerInterface], weights: Dict[str, float], token_list: List[str] | None = None, maxlenratio: float = 0.0, minlenratio: float = 0.0, pre_beam_ratio: float = 1.5, pre_beam_score_key: str = 'full') → list

Perform beam search with scorers.

• Parameters:
  • x (torch.Tensor) – Encoded speech feature (T, D)
  • sos (int) – Start of sequence id
  • eos (int) – End of sequence id
  • beam_size (int) – The number of hypotheses kept during search
  • vocab_size (int) – The number of vocabulary
  • scorers (dict *[*str , ScorerInterface ]) – Dict of decoder modules e.g., Decoder, CTCPrefixScorer, LM The scorer will be ignored if it is None
  • weights (dict *[*str , float ]) – Dict of weights for each scorers The scorer will be ignored if its weight is 0
  • token_list (list *[*str ]) – List of tokens for debug log
  • maxlenratio (float) – Input length ratio to obtain max output length. If maxlenratio=0.0 (default), it uses a end-detect function to automatically find maximum hypothesis lengths
  • minlenratio (float) – Input length ratio to obtain min output length.
  • pre_beam_score_key (str) – key of scores to perform pre-beam search
  • pre_beam_ratio (float) – beam size in the pre-beam search will be int(pre_beam_ratio * beam_size)
• Returns: N-best decoding results
• Return type: list