README.md

---
license: cc-by-nc-4.0
language:
- en
- de
- es
- sw
- ha
- yo
- zu
multilinguality:
- multilingual
task_categories:
- automatic-speech-recognition
- audio-classification
- text-to-speech
tags:
- voice-ai
- speech-data
- accent
- emotion
- african-languages
- multilingual
- asr
- tts
- conversational-ai
- real-world-audio
- crowdsourced
pretty_name: "🎙️ Silencio Voice AI Sample Dataset"
dataset_info:
  features:
  - name: file_name
    dtype: string
  - name: id
    dtype: int64
  - name: gender
    dtype: string
  - name: ethnicity
    dtype: string
  - name: occupation
    dtype: string
  - name: country_code
    dtype: string
  - name: birth_place
    dtype: string
  - name: mother_tongue
    dtype: string
  - name: dialect
    dtype: string
  - name: year_of_birth
    dtype: int64
  - name: years_at_birth_place
    dtype: int64
  - name: languages_data
    dtype: string
  - name: os
    dtype: string
  - name: device
    dtype: string
  - name: browser
    dtype: string
  - name: duration
    dtype: float64
  - name: emotions
    dtype: string
  - name: language
    dtype: string
  - name: location
    dtype: string
  - name: noise_sources
    dtype: string
  - name: script_id
    dtype: int64
  - name: type_of_script
    dtype: string
  - name: script
    dtype: string
  - name: transcript
    dtype: string
  - name: speaker_id
    dtype: string
configs:
- config_name: spanish_mexico
  data_files:
  - split: free_speech
    path: spanish_mexico/free_speech/**
  - split: keywords
    path: spanish_mexico/keywords/**
  - split: monologues
    path: spanish_mexico/monologues/**
- config_name: english_china
  data_files:
  - split: free_speech
    path: english_china/free_speech/**
  - split: keywords
    path: english_china/keywords/**
  - split: monologues
    path: english_china/monologues/**
- config_name: english_nigeria
  data_files:
  - split: free_speech
    path: english_nigeria/free_speech/**
  - split: keywords
    path: english_nigeria/keywords/**
  - split: monologues
    path: english_nigeria/monologues/**
- config_name: english_united_states
  data_files:
  - split: free_speech
    path: english_united_states/free_speech/**
  - split: keywords
    path: english_united_states/keywords/**
  - split: monologues
    path: english_united_states/monologues/**
- config_name: german_germany
  data_files:
  - split: free_speech
    path: german_germany/free_speech/**
  - split: keywords
    path: german_germany/keywords/**
  - split: monologues
    path: german_germany/monologues/**
size_categories:
- n<1K
---

# 🎙️ Silencio Network: Voice AI Sample Dataset

<p align="left">
  <img src="https://cdn-uploads.huggingface.co/production/uploads/69162b50b89e7abe20de4b5a/LWhs4p2lPFcyiVsP0tluu.png" width="40%">
</p>

[![Website](https://img.shields.io/badge/Website-silencioai.com-blue?style=flat-square)](https://www.silencioai.com)
[![Contact](https://img.shields.io/badge/Contact-sofia@silencioai.com-green?style=flat-square)](mailto:sofia@silencioai.com)
[![Data Available](https://img.shields.io/badge/Full_Corpus-100,000+_hours-orange?style=flat-square)](mailto:sofia@silencioai.com)

---

> **📊 This is a sample.** The full Silencio corpus contains **100,000+ hours** across **170+ countries** and **100+ languages**.
> 
> **📧 Contact:** [sofia@silencioai.com](mailto:sofia@silencioai.com) for custom datasets, bulk licensing, or specific language requests.

---

## 🌍 Why Silencio Data?

Silencio data is collected **in the wild** from a massive, opt-in community (**2M+ contributors** across **180+ countries**), giving you:

- ✅ **Real-world accents, dialects, devices, and environments** that lab or scraped datasets don't capture
- ✅ **Explicit, traceable consent** — every recording tied to verified opt-in (GDPR/CCPA compliant)
- ✅ **Privacy-first pipelines** — anonymized, PII hashed, reduced legal risk for enterprise
- ✅ **Rapid scaling** into hard-to-source languages and niches

## 📊 Full Data Availability

| Category | Available | Top Languages |
|----------|-----------|---------------|
| **African Languages** | 25,000+ hrs | Swahili (9.7k), Nigerian English (8.1k), Hausa, Yoruba, Zulu |
| **Asian Languages** | 15,000+ hrs | Hindi, Mandarin, Japanese, Korean, Vietnamese |
| **European Languages** | 20,000+ hrs | German, Spanish, French, Portuguese, Polish |
| **Emotional Speech** | 5,000+ hrs | Joy, anger, sadness, fear, surprise, neutral |
| **Multi-Speaker** | 10,000+ hrs | Overlapping speech, turn-taking, interruptions |
| **Conversational** | 30,000+ hrs | Natural dialogue, disfluencies, backchannels |

**Custom requests?** We can source virtually any language, accent, or demographic at scale.

---

## 🎯 This Sample Dataset

This sample covers **five language–region pairs** demonstrating our data quality:

| Config | Language | Accent/Region | Recordings | Duration |
|--------|----------|---------------|------------|----------|
| `english_nigeria` | English | Nigerian | 75 | 1.01 hrs |
| `english_china` | English | Mandarin-influenced | 75 | 0.96 hrs |
| `english_united_states` | English | American | 75 | 0.80 hrs |
| `spanish_mexico` | Spanish | Mexican | 56 | 0.77 hrs |
| `german_germany` | German | Native German | 75 | 0.73 hrs |
| **Total** | | | **356** | **4.29 hrs** |

## 🚀 Quick Start

```python
from datasets import load_dataset

# Load Nigerian English samples
ds = load_dataset("SilencioNetwork/voiceai-sample-speech-dataset", "english_nigeria")

# Access different speech types
free_speech = ds['free_speech']
keywords = ds['keywords']
monologues = ds['monologues']

# Process a sample
for sample in free_speech:
    audio = sample['audio']
    transcript = sample['transcript']
    speaker_id = sample['speaker_id']
    emotion = sample['emotions']
    print(f"Speaker {speaker_id}: {transcript[:50]}...")
```

## 🎤 Speech Types

| Type | Description | Use Cases |
|------|-------------|-----------|
| `free_speech` | Unscripted speech on provided topics | Conversational AI, dialogue systems |
| `keywords` | Short isolated phrases/terms | Wake word detection, command recognition |
| `monologues` | Longer scripted passages | TTS training, ASR benchmarking |

## 📋 Rich Metadata

Every recording includes:

- **Speaker demographics**: gender, ethnicity, occupation, birth year, birth place
- **Linguistic info**: mother tongue, dialect, language proficiency data
- **Recording context**: device, OS, browser, location, background noise
- **Content**: script, Whisper-generated transcript, emotion labels
- **Technical**: duration, 48kHz WAV format

## 🎯 Ideal For

- 🗣️ **ASR training** — accent-robust speech recognition
- 🔊 **TTS development** — diverse voice synthesis
- 😊 **Emotion recognition** — labeled emotional speech
- 🌍 **Multilingual models** — 100+ languages available
- 🎙️ **Speaker verification** — unique speaker embeddings
- 📊 **Benchmarking** — real-world robustness testing

## ⚖️ License

**CC BY-NC 4.0** — Free for research and non-commercial use.

For **commercial licensing**, contact [sofia@silencioai.com](mailto:sofia@silencioai.com).

## 📧 Get More Data

**Need the full corpus?** This sample represents <0.01% of our available data.

| What You Need | We Can Provide |
|---------------|----------------|
| Specific language/accent | ✅ 100+ languages available |
| Emotional speech | ✅ 5,000+ hours labeled |
| Multi-speaker/overlapping | ✅ 10,000+ hours |
| Custom demographics | ✅ Age, gender, occupation targeting |
| Bulk volume | ✅ 100,000+ hours total |

**📧 Email:** [sofia@silencioai.com](mailto:sofia@silencioai.com)

**🌐 Website:** [silencioai.com](https://www.silencioai.com)

---

## Citation

```bibtex
@dataset{silencio_network_speech_2025,
    title        = {Silencio Network Voice AI Speech Corpus},
    author       = {Silencio Network},
    year         = {2025},
    publisher    = {Hugging Face},
    license      = {CC BY-NC 4.0}
}
```