Audio Datasets
Collection
My training datasets for ASR fine tuning • 7 items • Updated
Datasets:
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 212, in _split_generators
raise ValueError(
f"Metadata files {downloaded_metadata_file} and {features_per_metadata_file[0][0]} have different features: {features_per_metadata_file[0]} != {metadata_features}"
)
ValueError: Metadata files hf://datasets/danielrosehill/Tech-Sentences@6c586d591c6d0b4088f3347ce4ed24ab3ebad11c/data/test/metadata.jsonl and hf://datasets/danielrosehill/Tech-Sentences@6c586d591c6d0b4088f3347ce4ed24ab3ebad11c/data/train/metadata.jsonl have different features: ('hf://datasets/danielrosehill/Tech-Sentences@6c586d591c6d0b4088f3347ce4ed24ab3ebad11c/data/train/metadata.jsonl', {'file_name': Value('string'), 'id': Value('string'), 'text': Value('string'), 'text_he': Value('string'), 'duration_s': Value('float64'), 'categories': List(Value('string')), 'target_terms': List(Value('string')), 'prompt_id': Value('string'), 'prompt_source': Value('string'), 'prompt_origin': Value('string'), 'mode': Value('string'), 'edited': Value('bool'), 'device': Value('string'), 'microphone': Value('string'), 'environment': Value('string'), 'conditions': List(Value('string')), 'noise_level': Value('null'), 'background_speech_languages': List(Value('null')), 'noise_flags': List(Value('null')), 'clipped': Value('bool'), 'notes': Value('null'), 'hebrew_pronunciation': Value('null'), 'variant_groups': List(Value('null')), 'variant_spelling': Value('null'), 'task': Value('string'), 'priority_word': Value('string'), 'spoken_text': Value('string'), 'aside_text': Value('null'), 'aside_position': Value('null'), 'verbatim_text': Value('null'), 'prompt_categories': Value('null'), 'source_prompt_id': Value('null'), 'prompt_kind': Value('null'), 'prompt_note': Value('null'), 'term_language': Value('null'), 'paragraph_text': Value('null'), 'model_hypothesis': Value('null'), 'asr_model': Value('null'), 'speaker': Value('string'), 'contributor': Value('string'), 'speaker_gender': Value('string'), 'sample_rate': Value('int64'), 'bit_depth': Value('int64'), 'audio_format': Value('string'), 'native_rate': Value('int64'), 'capture_mode': Value('string'), 'tts_eligible': Value('bool'), 'tts_split': Value('string'), 'transcript_status': Value('string'), 'prompt_set': Value('string'), 'topic': Value('null'), 'style': Value('string'), 'style_instruction': Value('null'), 'written_form_uncertain': Value('null'), 'session_id': Value('string'), 'room_tone_id': Value('string'), 'room': Value('string'), 'location': Value('string'), 'location_name': Value('null'), 'location_note': Value('null'), 'latitude': Value('null'), 'longitude': Value('null'), 'location_accuracy_m': Value('null'), 'lead_trim_s': Value('float64'), 'peak_dbfs': Value('float64'), 'floor_dbfs': Value('float64'), 'speech_dbfs': Value('float64'), 'snr_db': Value('float64'), 'clipped_samples': Value('int64'), 'edge_head_dbfs': Value('float64'), 'edge_tail_dbfs': Value('float64'), 'browser_processing': Value('bool'), 'recorded_at': Value('string'), 'text_full': Value('null'), 'fallback_ok': Value('null'), 'text_before_normalization': Value('string')}) != {'file_name': Value('string'), 'id': Value('string'), 'text': Value('string'), 'text_he': Value('string'), 'duration_s': Value('float64'), 'categories': List(Value('string')), 'target_terms': List(Value('string')), 'prompt_id': Value('string'), 'prompt_source': Value('string'), 'prompt_origin': Value('string'), 'mode': Value('string'), 'edited': Value('bool'), 'device': Value('string'), 'microphone': Value('string'), 'environment': Value('string'), 'conditions': List(Value('null')), 'noise_level': Value('null'), 'background_speech_languages': List(Value('null')), 'noise_flags': List(Value('null')), 'clipped': Value('bool'), 'notes': Value('null'), 'hebrew_pronunciation': Value('null'), 'variant_groups': List(Value('null')), 'variant_spelling': Value('null'), 'task': Value('string'), 'priority_word': Value('string'), 'spoken_text': Value('string'), 'aside_text': Value('null'), 'aside_position': Value('null'), 'verbatim_text': Value('null'), 'prompt_categories': Value('null'), 'source_prompt_id': Value('null'), 'prompt_kind': Value('null'), 'prompt_note': Value('null'), 'term_language': Value('null'), 'paragraph_text': Value('null'), 'model_hypothesis': Value('null'), 'asr_model': Value('null'), 'speaker': Value('string'), 'contributor': Value('string'), 'speaker_gender': Value('string'), 'sample_rate': Value('int64'), 'bit_depth': Value('int64'), 'audio_format': Value('string'), 'native_rate': Value('int64'), 'capture_mode': Value('string'), 'tts_eligible': Value('bool'), 'tts_split': Value('string'), 'transcript_status': Value('string'), 'prompt_set': Value('string'), 'topic': Value('null'), 'style': Value('string'), 'style_instruction': Value('null'), 'written_form_uncertain': Value('null'), 'session_id': Value('string'), 'room_tone_id': Value('string'), 'room': Value('string'), 'location': Value('string'), 'location_name': Value('null'), 'location_note': Value('null'), 'latitude': Value('null'), 'longitude': Value('null'), 'location_accuracy_m': Value('null'), 'lead_trim_s': Value('float64'), 'peak_dbfs': Value('float64'), 'floor_dbfs': Value('float64'), 'speech_dbfs': Value('float64'), 'snr_db': Value('float64'), 'clipped_samples': Value('int64'), 'edge_head_dbfs': Value('float64'), 'edge_tail_dbfs': Value('float64'), 'browser_processing': Value('bool'), 'recorded_at': Value('string'), 'text_full': Value('null'), 'fallback_ok': Value('null'), 'text_before_normalization': Value('string')}
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 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/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.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Tech Sentences
Dictation-style English sentences dense in software, DevOps, cloud, self-hosting and AI vocabulary (product names, CLI tools, acronyms, model names), read aloud by one speaker. Terms use the vendor's own casing (GitHub, PostgreSQL, kubectl). Includes long-form dictation of instructions to AI coding agents. Sentences that also code-switch into Hebrew are not included (since 2026-10-19); they are in English-Hebrew-Codeswitching-Sentences.
Website: hebrish.app: get the Hebrish keyboard for Android and the desktop apps, see the results, and find every model, dataset and demo in one place.
This is a subset of danielrosehill/Read-Aloud-Voice-Sentences, the full, undifferentiated
dataset. It contains every phone recording there whose categories include tech and not code_switch. Rows are copied
unchanged, with the same ids, columns and train/test split, by scripts/sync_subsets.py in the
project repository. Do not edit this dataset directly: fix the row in the main dataset and re-sync.
The subset grows as new takes are published.
Speaker: Daniel Rosehill, the dataset's author, who was born in Ireland and speaks English with an Irish accent, and who lives in Jerusalem. Every recording is his voice. Deliberate variation: he sometimes changes his speaking speed on purpose (fast and rushed, or slow) and sometimes says a word the way people commonly mispronounce it, to make the models robust to real speech. The transcript is always the sentence as written, so a take whose speed or pronunciation sounds off against its card is usually intentional, not a recording error.
All audio was recorded on a OnePlus Nord 3 5G phone using its internal microphone, with browser echo cancellation, noise suppression and auto gain turned off.
Layout
data/train/audio/<id>.flac 48 kHz mono 24-bit FLAC (rows from 2026-10-22)
data/train/audio/<id>.wav 16 kHz mono 16-bit PCM (earlier rows)
data/train/metadata.jsonl
data/test/... held-out set, never trained on
The test split is term-disjoint: a held-out term never appears in train.
load_dataset("danielrosehill/Tech-Sentences") works directly.
Columns
The columns are the same as in the main dataset: text (ground truth, punctuated and cased like
Parakeet v2 output), text_he (the same transcript with its Hebrew terms in Hebrew script, for
Hebrew-capable models), categories, target_terms, prompt_source, prompt_origin (manual / dataset / generated), edited, duration_s,
environment, conditions, device, speaker, speaker_gender, contributor, hebrew_pronunciation, variant_groups, variant_spelling and recorded_at. The main dataset's card describes them.
Licence
CC-BY-4.0, with sentence-text attribution per prompt_source as described in the
main dataset's licence section.
- Downloads last month
- 538