Datasets:

united-nations
/

transcription-results

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 236, in _generate_tables
                  pa_table = paj.read_json(
                             ^^^^^^^^^^^^^^
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 93, in _split_generators
                  pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 250, in _generate_tables
                  batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/utils/json.py", line 90, in json_encode_fields_in_json_lines
                  examples = [ujson_loads(line) for line in original_batch.splitlines()]
                              ^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/utils/json.py", line 20, in ujson_loads
                  return pd.io.json.ujson_loads(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
              ValueError: Expected object or value
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                         ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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UN Transcription Benchmark Results

Evaluation results for speech-to-text systems on UN Security Council and General Assembly meeting recordings, assessed against official UN verbatim records.

See united-nations/transcription-corpus for the underlying audio and ground truth data.

Metrics

WER: Word Error Rate (reference = verbatim record, no normalization)
normalized_wer: WER after lowercasing, punctuation removal, and filler word removal
CER: Character Error Rate (same reference, no normalization)
normalized_cer: CER after normalization

Note: WER of 20–40% is expected for high-quality transcription on these recordings due to the editing gap between live speech and published verbatim records. For Chinese, use CER as the primary metric (Chinese text has no word boundaries).

Providers Evaluated

Provider	Model	Pricing
`assemblyai`	AssemblyAI Universal-2 (diarization enabled)	~$0.17/hr
`azure-openai`	Azure OpenAI gpt-4o-transcribe-diarize	~$0.36/hr
`elevenlabs`	ElevenLabs Scribe v2	~$0.40/hr
`azure-speech`	Azure Cognitive Services Speech Batch Transcription	~$0.36/hr
`gemini`	Gemini 3 Flash (structured diarization via prompt)	~$0.01/hr
`google-chirp`	Google Cloud Chirp 3 (Speech V2 API)	~$0.016/min
`groq-whisper`	Whisper large-v3 (via Groq)	~$0.015/min

Schema

Column	Type	Description
symbol	string	UN document symbol, e.g. `S/PV.10100`
assetId	string	UN Web TV asset ID
language	string	ISO 639-1 code
provider	string	Transcription provider name
wer	float	Word Error Rate (0–1)
normalized_wer	float	Normalized WER (0–1)
cer	float	Character Error Rate (0–1)
normalized_cer	float	Normalized CER (0–1)
substitutions	int	Number of word substitutions
insertions	int	Number of word insertions
deletions	int	Number of word deletions
ref_length	int	Reference word count
hyp_length	int	Hypothesis word count
duration_ms	int	Audio duration in ms
timestamp	string	ISO 8601 evaluation timestamp

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