Datasets:

KeisukeMiyamoto
/

lambda-audio-courpus

pretty_name: Lambda Audio Corpus
annotations_creators:
  - machine-generated
language_creators:
  - found
language:
  - ja
multilinguality:
  - monolingual
source_datasets:
  - KeisukeMiyamoto/nhk-archive-audio-30s
  - KeisukeMiyamoto/nhk-radio-news-audio-30s
  - reazon-research/reazonspeech
  - KeisukeMiyamoto/tech-podcast-audio-30s
task_categories:
  - automatic-speech-recognition
tags:
  - audio
  - speech
  - japanese
  - asr
  - broadcast
  - news
  - podcast
  - reazonspeech
  - flac
size_categories:
  - 1M<n<10M
license: other
dataset_info:
  - config_name: default
    features:
      - name: id
        dtype: string
      - name: audio
        dtype:
          audio:
            sampling_rate: 16000
      - name: text
        dtype: string
      - name: raw_text
        dtype: string
      - name: speech_segments
        list:
          - name: start
            dtype: float64
          - name: end
            dtype: float64
      - name: has_speech
        dtype: bool
      - name: duration
        dtype: float64
      - name: prev_id
        dtype: string
      - name: prev_text
        dtype: string
      - name: origin
        dtype: string
    splits:
      - name: train
        num_examples: 2330321
      - name: test
        num_examples: 11776
      - name: validation
        num_examples: 11776
configs:
  - config_name: default
    data_files:
      - split: train
        path: train/*.parquet
      - split: test
        path: test/*.parquet
      - split: validation
        path: validation/*.parquet

Lambda Audio Corpus

This is a combined Japanese automatic speech recognition corpus containing 2,353,873 clips (8,592.83 hours). It combines archive, podcast, and ReazonSpeech data in a common schema. Audio is embedded as 16 kHz mono FLAC, and stored durations range from 0.46 to 30 seconds.

Sources

`origin`	Included clips	Duration	Source
`nhk-archive-audio-30s`	137,106	1,067.26 hours	NHK Archives Audio 30s
`reazon-speech-v2`	1,023,030	1,821.55 hours	ReazonSpeech v2
`tech-podcast-audio-30s`	1,127,635	5,509.03 hours	Tech Podcast Audio 30s

The table describes the records included here and does not imply that every upstream dataset is included in full.

Splits

Split	Clips	Duration	Ratio by rows
train	2,330,321	8,506.72 hours	99.00%
test	11,776	43.35 hours	0.50%
validation	11,776	42.76 hours	0.50%

Complete Parquet files were assigned to splits to approximate the target row ratios. The input rows were shuffled with seed 42 before files were assigned. The splits are not speaker-, program-, episode-, or source-disjoint.

Columns

Column	Description
`id`	Unique segment ID.
`audio`	Embedded 16 kHz mono FLAC audio.
`text`	Transcript used as the ASR target. Its provenance and correction process depend on `origin`.
`raw_text`	Transcript before correction, when supplied by the source dataset. It is null for `reazon-speech-v2`.
`speech_segments`	Speech intervals in seconds relative to the stored clip.
`has_speech`	Whether speech is present; true for all included records.
`duration`	Stored clip duration in seconds.
`prev_id`	Previous related segment ID, when available.
`prev_text`	Transcript of the previous related segment, when available.
`origin`	Source dataset identifier shown in the Sources table.

For the NHK and podcast sources, raw_text was generated with Whisper large-v3-turbo and text contains LLM-assisted corrections. For reazon-speech-v2, text is derived from the supplied ReazonSpeech transcription and raw_text is unavailable. A record referenced by prev_id may be in another split or may have been removed during filtering or deduplication; prev_text can therefore cause contextual leakage.

Usage

from datasets import load_dataset

dataset = load_dataset(
    "KeisukeMiyamoto/lambda-audio-courpus",
    split="train",
    streaming=True,
)

record = next(iter(dataset))
print(record["id"], record["origin"], record["duration"], record["text"])

Streaming is recommended because the Parquet files occupy approximately 575.0 GiB.

Source Terms and License

This combined dataset uses license: other because rights and conditions differ by source. Copyright in the original recordings remains with the respective creators and rights holders.

NHK-derived data remains subject to the applicable NHK terms, including the NHK Creative Library usage rules.
ReazonSpeech is distributed under CDLA-Sharing-1.0 and its dataset card additionally restricts use to the purpose permitted by Article 30-4 of the Japanese Copyright Act. Review and accept the ReazonSpeech terms before use.
Podcast recordings remain the property of their creators and publishers; users must verify that their intended use is permitted.

Users are responsible for reviewing every upstream dataset card and ensuring compliance with all applicable licenses, terms, copyright restrictions, privacy requirements, and laws.