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  **Utterly** is a speech dataset derived from *pipecat-ai/human_5_all*. It contains **~3.86k English utterances** by a broad range of speakers, and augments conversational audio 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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  ## Source Data
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- * **Base dataset**: pipecat-ai/human_5_all
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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**: 3,860
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- * **Speakers**: 100+
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  Dataset splits (e.g., train/validation/test) are not predefined and may be created by downstream users as needed.
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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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  * `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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- Depending on downstream usage, additional metadata from the source dataset may also be present.
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-
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  ---
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  ## Intended Use Cases
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  ## Citation
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- If you use the Utterly dataset in academic or commercial work, please reference the original *pipecat-ai/human_5_all* dataset.
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- ---
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-
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- Future versions may include additional annotations, languages, or refined turn boundary definitions.
 
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  **Utterly** is a speech dataset derived from *pipecat-ai/human_5_all*. It contains **~3.86k English utterances** by a broad range of speakers, and augments conversational audio 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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  ## Source Data
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+ * **Base dataset**: *pipecat-ai/human_5_all*
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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**: 3,860
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+ * **Speakers**: >100
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  Dataset splits (e.g., train/validation/test) are not predefined and may be created by downstream users as needed.
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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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  * `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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  ## Intended Use Cases
 
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  ## Citation
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+ If you use the Utterly dataset in academic or commercial work, please reference the original *pipecat-ai/human_5_all* dataset.