---
language:
- hi
tags:
- audio
- speech
- automatic-speech-recognition
- speech-recognition
task_categories:
- automatic-speech-recognition
pretty_name: Poseidon Hindi Speech Samples
size_categories:
- 1K<n<10K
dataset_info:
  features:
  - name: audio
    dtype: audio
  - name: file_id
    dtype: string
  - name: speaker_id
    dtype: string
  - name: language_code
    dtype: string
  - name: GT_transcript_english
    dtype: string
  - name: GT_transcript_native
    dtype: string
  - name: spoken_transcript_native
    dtype: string
  - name: spoken_transcript_english
    dtype: string
  - name: wer_score
    dtype: float64
  - name: cer_score
    dtype: float64
  - name: semantic_score
    dtype: float64
  - name: poseidon_score
    dtype: float64
  - name: duration
    dtype: float64
  - name: sampling_rate
    dtype: int64
  - name: embedding
    dtype: string
  - name: jitter
    dtype: float64
  splits:
  - name: train
    num_bytes: 1756655019
    num_examples: 2500
  download_size: 1750962836
  dataset_size: 1756655019
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# Poseidon Hindi Speech Dataset

## Dataset Description

This dataset contains 2,500 Hindi audio recordings from the Poseidon audio campaign.

### Dataset Statistics

- **Total Samples:** 2,500
- **Total Duration:** 42.72 hours
- **Average WER:** 0.5357
- **Average CER:** 0.3878
- **Average Semantic Score:** 0.9092
- **Average Poseidon Score:** 0.6941

### Decision Rules

- **Poseidon score** (`poseidon_score`) **> 0.55** (*higher the better*)

### Language Distribution

- **hi: 2,500 samples**

## Dataset Structure

### Data Fields

- `audio`: Audio file metadata and bytes
- `file_id`: Unique identifier for the audio file
- `speaker_id`: Unique identifier for the speaker
- `language_code`: ISO language code
- `GT_transcript_native`: Ground truth transcript in Hindi
- `GT_transcript_english`: Ground truth transcript in English
- `spoken_transcript_native`: ASR-generated transcript in Hindi
- `spoken_transcript_english`: ASR-generated transcript translated to English
- `wer_score`: Word Error Rate score (range: [0,1])
- `cer_score`: Character Error Rate score (range: [0,1])
- `semantic_score`: Semantic similarity score (range: [0,1])
- `poseidon_score`: Overall quality score (range: [0,1])
- `duration`: Audio duration in seconds
- `sampling_rate`: Audio sampling rate in Hz
- `embedding`: a 192 dimensional embedding generated from https://huggingface.co/speechbrain/spkrec-ecapa-voxceleb for the audio file
- `jitter`: Jitter (local absolute) percentage - voice quality metric measuring pitch period variation (range: 0.75-4.47%, mean: 1.62%)

### Data Splits

The dataset is delivered as a single `train` split (100% of the data).

## Usage

```python
from datasets import load_dataset

# Load the entire dataset
dataset = load_dataset("psdn-ai/psdn-voice-samples-hindi")

# Load specific split
train_data = load_dataset("psdn-ai/psdn-voice-samples-hindi", split="train")

# Access audio and metadata
sample = dataset["train"][0]
audio_array = sample["audio"]["array"]
sampling_rate = sample["audio"]["sampling_rate"]
transcript = sample["GT_transcript"]
duration = sample["duration"]
```

## Quality Metrics

This dataset bundles multiple quality indicators:

- **WER (Word Error Rate):** Measures word-level transcription accuracy
- **CER (Character Error Rate):** Measures character-level transcription accuracy
- **Semantic Score:** Measures semantic similarity between spoken and reference transcripts
- **Poseidon Score:** Composite quality score derived from the above metrics

## Filtering Examples

```python
from datasets import load_dataset

dataset = load_dataset("psdn-ai/psdn-voice-samples-hindi", split="train")

# Filter clips with low spam probability
human_sounding = dataset.filter(lambda x: x["poseidon_score"] > 0.55)
```

## Citation

```bibtex
@dataset{poseidon_hindi_speech_dataset_2025,
  title={Poseidon Hindi Speech Dataset},
  author={Poseidon-AI},
  year={2025},
  publisher={Poseidon-AI},
  howpublished={\url{https://huggingface.co/datasets/psdn-ai/psdn-voice-samples-hindi}}
}
```

## Contact

For questions or issues, please contact Poseidon team.