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Datasets:
hiraki
/
candor-turntaking-annotations

Tasks:
Automatic Speech Recognition
Modalities:
Tabular
Text
Formats:
parquet
Languages:
English
Size:
100K - 1M
Tags:
speech
transcription
conversation
turn-taking
candor
canary
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
xet
 Community
1
Dataset Viewer
Auto-converted to Parquet Duplicate
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
audio_filename: string
offset: double
duration: double
segment_id: string
conversation_id: string
channel: string
text: string
model: string
alignment_mean_prob: double
tt_label: string
tt_confidence: double
llm_label: string
llm_confidence: double
llm_rationale: string
final_tag: string
accepted: null
accept_reason: string
reject_reason: string
silence_after_ms: double
overlap_ratio: double
prev_same_speaker: string
next_same_speaker: string
prev_other_speaker: string
next_other_speaker: string
-- schema metadata --
pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 3072
to
{'audio_filename': Value('string'), 'offset': Value('float64'), 'duration': Value('float64'), 'segment_id': Value('string'), 'conversation_id': Value('string'), 'channel': Value('string'), 'text': Value('string'), 'model': Value('string'), 'alignment_mean_prob': Value('float64'), 'tt_label': Value('string'), 'tt_confidence': Value('float64'), 'llm_label': Value('string'), 'llm_confidence': Value('float64'), 'llm_rationale': Value('string'), 'final_tag': Value('string'), 'accepted': Value('bool'), 'accept_reason': Value('string'), 'reject_reason': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/parquet/parquet.py", line 209, in _generate_tables
                  yield Key(file_idx, batch_idx), self._cast_table(pa_table)
                                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/parquet/parquet.py", line 147, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              audio_filename: string
              offset: double
              duration: double
              segment_id: string
              conversation_id: string
              channel: string
              text: string
              model: string
              alignment_mean_prob: double
              tt_label: string
              tt_confidence: double
              llm_label: string
              llm_confidence: double
              llm_rationale: string
              final_tag: string
              accepted: null
              accept_reason: string
              reject_reason: string
              silence_after_ms: double
              overlap_ratio: double
              prev_same_speaker: string
              next_same_speaker: string
              prev_other_speaker: string
              next_other_speaker: string
              -- schema metadata --
              pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 3072
              to
              {'audio_filename': Value('string'), 'offset': Value('float64'), 'duration': Value('float64'), 'segment_id': Value('string'), 'conversation_id': Value('string'), 'channel': Value('string'), 'text': Value('string'), 'model': Value('string'), 'alignment_mean_prob': Value('float64'), 'tt_label': Value('string'), 'tt_confidence': Value('float64'), 'llm_label': Value('string'), 'llm_confidence': Value('float64'), 'llm_rationale': Value('string'), 'final_tag': Value('string'), 'accepted': Value('bool'), 'accept_reason': Value('string'), 'reject_reason': Value('string')}
              because column names don't match

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CANDOR - Turn-Taking Annotations

Speech transcription and turn-taking annotation dataset built from the CANDOR corpus using NVIDIA Canary-Qwen2.5B ASR.

Dataset Description

This dataset contains 172,591 transcribed speech segments from the CANDOR conversational speech corpus (1,656 conversations). Each segment is a per-speaker utterance with Canary ASR transcript, designed for turn-taking prediction research.

Source

  • Audio corpus: CANDOR (English conversational speech, 1,656 conversations)
  • ASR model: NVIDIA Canary-Qwen2.5B (canary-qwen-2.5b)
  • Audio format: Per-speaker mono WAV (16kHz), extracted from stereo MP3

Dataset Structure

Column Type Description
audio_filename string Per-speaker WAV filename (e.g., {uuid}_L.wav)
offset float Start time within the audio file (seconds)
duration float Duration of the segment (seconds)
segment_id string Unique segment identifier
conversation_id string CANDOR conversation UUID
channel string Speaker channel (L or R)
text string Canary ASR transcript
model string ASR model (canary-qwen-2.5b)
alignment_mean_prob float Parakeet CTC forced alignment score (to be added)
tt_label string TEN turn-taking label: finished/unfinished/wait (to be added)
tt_confidence float TEN confidence (3-way softmax) (to be added)
llm_label string LLM label: COMPLETE/INCOMPLETE/BACKCHANNEL (to be added)
llm_confidence float LLM confidence (to be added)
llm_rationale string LLM reasoning (to be added)
final_tag string Cross-annotation consensus label (to be added)
accepted bool Whether segment passed all quality gates (to be added)
accept_reason string Reason for acceptance (to be added)
reject_reason string Reason for rejection (to be added)

Annotation Pipeline (in progress)

Annotations are being added incrementally:

  1. Parakeet CTC forced alignment → alignment_mean_prob
  2. TEN turn-taking model → tt_label, tt_confidence
  3. LLM annotation (Qwen2.5-32B) → llm_label, llm_confidence, llm_rationale
  4. Cross-annotation → final_tag, accepted (requires tt_confidence >= 0.9, alignment_mean_prob >= 0.9)

Statistics

  • Total segments: 172,591
  • Conversations: 1,656
  • Segments with text: 165,925 (96.1%)
  • Mean duration: 7.6s

Intended Use

This dataset is intended for research on:

  • Turn-taking prediction and modeling
  • Conversational speech recognition
  • Backchannel detection

Related Datasets

License

CC-BY-4.0 (following the CANDOR corpus license).
Downloads last month
22
Size of downloaded dataset files:
36.1 MB
Size of the auto-converted Parquet files:
36.1 MB
Number of rows:
172,591