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--- |
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dataset_info: |
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features: |
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- name: source |
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dtype: string |
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- name: audio |
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dtype: audio |
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- name: is_complete |
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dtype: bool |
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- name: transcript |
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dtype: string |
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splits: |
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- name: train |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/* |
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license: bsd-2-clause |
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task_categories: |
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- automatic-speech-recognition |
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- voice-activity-detection |
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language: |
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- en |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Utterly |
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## Dataset Summary |
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**Utterly** is a speech dataset derived from *pipecat-ai/human_5_all* and *pipecat-ai/smart-turn-data-v3.1-train*. It contains over **7.1k recordings of complete and partial English utterances**, each augmented with **turn-level annotations**, including: |
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* Verbatim Whisper-generated transcripts |
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* End-of-turn (EoT) markers |
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* Speaker identifiers (Coming soon) |
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The dataset is designed to support research and development of speech and dialogue systems that require joint modeling of **speech recognition** and **conversational turn-taking**, such as streaming ASR systems, semantic end-of-turn detection and real-time conversational agents. |
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--- |
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## Source Data |
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* **Base datasets**: |
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- *pipecat-ai/human_5_all* |
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- *pipecat-ai/smart-turn-data-v3.1-train* |
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* **Language(s)**: English |
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* **Modality**: Audio (speech; mono-channel; sampled at 16kHz), Text |
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* **Interaction type**: Human conversational speech |
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* **Utterances**: 7,111 |
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* **Speakers**: 500+ |
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Dataset splits (e.g., train/validation/test) are not predefined and may be created by downstream users as needed. Deduplication was applied to the underlying audio sources to ensure dataset splits can be made without contamination. |
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--- |
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## Annotation Details |
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* **Transcripts** |
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* Generated automatically using **Whisper Large V3 Turbo**. |
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* A subset of samples (\~200) was manually reviewed and corrected. The transcripts are estimated to have approximately a word error rate (WER) of **\~2.8%**. |
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* **End-of-Turn markers** |
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* Human annotations inherited from the base datasets. |
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* **Speaker IDs** |
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* Coming soon |
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--- |
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## Dataset Structure |
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A typical data entry includes: |
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* `audio`: Path or reference to the audio utterance |
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* `transcript`: Text transcription of the utterance |
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* `speaker_id`: Identifier for the speaker (Coming soon) |
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* `is_completed`: Boolean or categorical flag indicating end-of-turn, i.e. turn completion |
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--- |
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## Usage |
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In order to load the dataset from the hub, you can use the `datasets` library: |
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```python |
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ds = datasets.load_dataset( |
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"ThBel/Utterly", |
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split='train', |
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streaming=True # (optional) |
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) |
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for row in ds: |
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# Do something with the data |
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print(row['audio']) # or row['is_complete'], row['transcript'], ... |
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``` |
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Alternatively you may clone the `ThBel/Utterly` repository, and load the underlying parquet files using `pandas.read_parquet`. |
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--- |
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## Intended Use Cases |
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The Utterly dataset is designed to support a range of speech and dialogue research tasks, including but not limited to: |
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* **Automatic Speech Recognition (ASR)** with embedded end-of-turn detection |
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* **Semantic end-of-turn modeling** using lexical and acoustic cues |
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* **Turn-taking and floor-control research** in conversational AI |
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* **Voice assistants and dialogue systems** requiring low-latency response timing |
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--- |
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## Quality Considerations |
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* End-of-turn annotations involve human judgment and may reflect subjective interpretations of conversational completion. |
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* Transcription quality may vary depending on audio clarity and source conditions. |
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* Overlapping speech, interruptions, or disfluencies may introduce ambiguity in turn boundaries. |
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Users are encouraged to validate performance across multiple evaluation settings. |
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--- |
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## Ethical Considerations |
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* The dataset consists of recorded human speech and should be used in accordance with the original dataset's licensing and consent terms. |
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* No additional personally identifying information beyond speaker IDs is introduced. |
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* Models trained on this dataset should avoid misuse related to surveillance or speaker profiling. |
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--- |
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## Disclaimer and Licensing |
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Note that Utterly is a *derived dataset*. I am not the original creator of the source datasets and hold no rights over its content. This dataset is provided as-is for research purposes, and all credit goes to the original authors. |
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Annotations are released under the **BSD-2-Clause** license and are intended to be compatible with the licensing terms of the source datasets. |
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--- |
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## Citation |
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If you use the Utterly dataset in academic or commercial work, please reference the original datasets. |
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