Datasets:

eko57
/

spc_r_segmented

dataset_info:
  features:
    - name: id
      dtype: string
    - name: duration
      dtype: float64
    - name: audio
      dtype: audio
    - name: text
      dtype: string
language:
  - de
task_categories:
  - automatic-speech-recognition
source_datasets:
  - i4ds/spc_r
license: cc-by-4.0

eko57/spc_r_segmented

Diarized and segmented speech dataset derived from i4ds/spc_r.

Description

Each row is a merged speech segment belonging to a single speaker. The source audio and SRT subtitles from i4ds/spc_r were processed with the following pipeline:

Diarization -- pyannote/speaker-diarization-3.1 assigned speaker labels to each SRT segment based on temporal overlap.
Merging -- Consecutive SRT segments from the same speaker were merged when the silence gap between them was below a threshold (default 1.0s) and the resulting duration stayed within bounds (default 10--20s).
Slicing -- The merged time ranges were used to slice the original audio waveform. Each segment is encoded as FLAC.

Columns

Column	Type	Description
`id`	string	Unique identifier (`row{NNNNN}_seg{NNN}`)
`duration`	float64	Segment duration in seconds
`audio`	audio	FLAC audio for the segment
`text`	string	Merged transcript text from the SRT segments

Usage

from datasets import load_dataset

ds = load_dataset("eko57/spc_r_segmented")
print(ds["train"][0])