espnet2.asr_transducer.frontend.online_audio_processor.OnlineAudioProcessor

source

class espnet2.asr_transducer.frontend.online_audio_processor.OnlineAudioProcessor(feature_extractor: Module, normalization_module: Module, decoding_window: int, encoder_sub_factor: int, frontend_conf: Dict, device: device, audio_sampling_rate: int = 16000)

Bases: object

OnlineProcessor module definition.

• Parameters:
  • feature_extractor – Feature extractor module.
  • normalization_module – Normalization module.
  • decoding_window – Size of the decoding window (in ms).
  • encoder_sub_factor – Encoder subsampling factor.
  • frontend_conf – Frontend configuration.
  • device – Device to pin module tensors on.
  • audio_sampling_rate – Input sampling rate.

Construct an OnlineAudioProcessor.

compute_features(samples: Tensor, is_final: bool) → None

Compute features from input samples.

• Parameters:
  • samples – Speech data. (S)
  • is_final – Whether speech corresponds to the final chunk of data.
• Returns: Features sequence. (1, chunk_sz_bs, D_feats) feats_length: Features length sequence. (1,)
• Return type: feats

get_current_feats(feats: Tensor, feats_length: Tensor, is_final: bool) → Tuple[Tensor, Tensor]

Get features for current decoding window.

• Parameters:
  • feats – Computed features sequence. (1, F, D_feats)
  • feats_length – Computed features sequence length. (1,)
  • is_final – Whether feats corresponds to the final chunk of data.
• Returns: Decoding window features sequence. (1, chunk_sz_bs, D_feats) feats_length: Decoding window features length sequence. (1,)
• Return type: feats

get_current_samples(samples: Tensor, is_final: bool) → Tensor

Get samples for feature computation.

• Parameters:
  • samples – Speech data. (S)
  • is_final – Whether speech corresponds to the final chunk of data.
• Returns: New speech data. (1, decoding_samples)
• Return type: samples

reset_cache() → None

Reset cache parameters.

• Parameters:None
• Returns: None