espnet3.components.metrics.base_metric.BaseMetric

source

class espnet3.components.metrics.base_metric.BaseMetric

Bases: ABC

Base class for metrics that consume inference output paths.

iter_inputs(data: Dict[str, Path], *keys: str) → Iterator[Tuple[str, Dict[str, str]]]

Yield rows from one or more SCP inputs with shared utterance IDs.

This helper reads one or more SCP files in lockstep. For a single key, it behaves as a streaming SCP iterator that returns (utt_id, row) pairs. For multiple keys, it additionally validates that all files contain the same utterance IDs in the same order. It is intended for metrics that want a single streaming API regardless of how many input files they consume.

• Parameters:
  • data (Dict *[*str , Path ]) – Mapping from input aliases to SCP paths.
  • *keys (str) – Input aliases to read together, e.g. ("ref",) or ("ref", "hyp").
• Yields:Iterator[Tuple[str, Dict[str, str]]] – Tuples of (utt_id, row), where row is an alias -> value mapping for that utterance.

  (
      "utt1",
      {"ref": "the cat", "hyp": "the bat"},
  )

• Raises:AssertionError – If no keys are provided, if one file has more entries than another, or if utterance IDs do not match across files.

Example

>>> for utt_id, row in self.iter_inputs(data, "ref", "hyp"):
...     print(utt_id, row["ref"], row["hyp"])
utt1 the cat the bat
utt2 a dog a dog

>>> for utt_id, row in self.iter_inputs(data, "ref"):
...     print(utt_id, row["ref"])
utt1 the cat
utt2 a dog

Notes

• Alignment is checked in file order.
• This helper does not sort utterance IDs.
• Each input is expected to be in SCP format:

  utt1 value
  utt2 another value