Upload README.md

README.md

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+---
+license: cc-by-nc-4.0
+language:
+- en
+- de
+- es
+multilinguality:
+- multilingual
+task_categories:
+- automatic-speech-recognition
+- audio-classification
+pretty_name: Multilingual Speech Sample
+dataset_info:
+- config_name: all_samples
+  features:
+  - 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: transcription_segments
+    dtype: string
+  - name: audio
+    dtype: audio
+  - name: speaker_id
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1196
+- config_name: english_united_states
+  splits:
+  - name: train
+    num_examples: 277
+- config_name: english_nigeria
+  splits:
+  - name: train
+    num_examples: 265
+- config_name: english_china
+  splits:
+  - name: train
+    num_examples: 185
+- config_name: german_germany
+  splits:
+  - name: train
+    num_examples: 328
+- config_name: spanish_mexico
+  splits:
+  - name: train
+    num_examples: 141
+configs:
+- config_name: all_samples
+  data_files:
+  - split: train
+    path: data/*/train-*.parquet
+- config_name: english_united_states
+  data_files:
+  - split: train
+    path: data/english_united_states/train-*.parquet
+- config_name: english_nigeria
+  data_files:
+  - split: train
+    path: data/english_nigeria/train-*.parquet
+- config_name: english_china
+  data_files:
+  - split: train
+    path: data/english_china/train-*.parquet
+- config_name: german_germany
+  data_files:
+  - split: train
+    path: data/german_germany/train-*.parquet
+- config_name: spanish_mexico
+  data_files:
+  - split: train
+    path: data/spanish_mexico/train-*.parquet
+size_categories:
+- 1K<n<10K
+---
+# Silencio Network: Multilingual Accent Speech Dataset (Sample)
+
+<p align="left">
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/69162b50b89e7abe20de4b5a/LWhs4p2lPFcyiVsP0tluu.png" width="40%">
+</p>
+
+## Overview
+
+Silencio data is valuable because it’s collected in the wild from a massive, opt-in community (1.2M users across 180+ countries), giving buyers real-world accents, dialects, devices, and environments that lab or scraped datasets don’t capture. Every recording is tied to explicit, traceable consent and processed with privacy-first pipelines (GDPR/CCPA compliant, anonymized, PII hashed), which reduces legal risk for enterprise buyers. On top of that, the same community lets us scale quickly into hard-to-source languages and niches, so clients get both authenticity today and a credible path to large volumes tomorrow.
+
+This dataset is a crowdsourced multilingual–accented English and non-English speech dataset designed for model training, benchmarking, and acoustic analysis. It emphasizes accent variation, short-form scripted prompts, and spontaneous free speech. All recordings were produced by contributors using their own devices, with Whisper-generated transcripts provided for every sample.
+
+The dataset is structured for direct use in ASR, TTS, accent-classification, diarization-adjacent analysis, speech segmentation, and embedding evaluation.
+
+## Languages and Accents
+This dataset covers five language–region pairs (to find out more about other combinations please reach out to us):
+
+- **English (China)**: English spoken with Mandarin-influenced accent  
+- **English (Nigeria)**: Nigerian-accented English  
+- **English (United States)**: American English  
+- **German (Germany)**: Native German speakers  
+- **Spanish (Mexico)**: Native Mexican Spanish speakers  
+
+All recordings are stored as **48 kHz WAV** files.
+
+## Speech Types
+Each sample belongs to one of three categories:
+
+- **free_speech**: unscripted speech on a provided topic  
+- **keywords**: short isolated prompts containing specific phrases or terms  
+- **monologues**: longer scripted passages  
+
+These values appear in the field `type_of_script`.
+
+## Recording Conditions
+All data is **crowdsourced**. Contributors record themselves using their available hardware and environment; conditions therefore vary naturally across microphones, devices, and noise profiles. No studio-grade normalisation or homogenisation is applied.
+
+## Transcription
+Transcriptions are machine-generated using **OpenAI Whisper**, preserving its segmentation structure where applicable. 
+
+## Dataset Statistics
+Durations are given in hours. Counts reflect samples within each `(language, region, type_of_script)` partition.
+
+### English (China)
+| type_of_script | duration_hrs | recordings | speakers |
+|----------------|--------------|------------|----------|
+| free_speech    | 0.99     | 72         | 19       |
+| keywords       | 0.48     | 57         | 10       |
+| monologues     | 0.98     | 56         | 11       |
+
+### English (Nigeria)
+| type_of_script | duration_hrs | recordings | speakers |
+|----------------|--------------|------------|----------|
+| free_speech    | 0.98     | 75         | 65       |
+| keywords       | 0.99     | 141        | 101      |
+| monologues     | 0.99     | 49         | 32       |
+
+### English (United States)
+| type_of_script | duration_hrs | recordings | speakers |
+|----------------|--------------|------------|----------|
+| free_speech    | 0.99     | 80         | 35       |
+| keywords       | 0.99     | 119        | 40       |
+| monologues     | 0.99     | 78         | 27       |
+
+### German (Germany)
+| type_of_script | duration_hrs | recordings | speakers |
+|----------------|--------------|------------|----------|
+| free_speech    | 0.98     | 99         | 34       |
+| keywords       | 0.99     | 152        | 37       |
+| monologues     | 0.98     | 77         | 27       |
+
+### Spanish (Mexico)
+| type_of_script | duration_hrs | recordings | speakers |
+|----------------|--------------|------------|----------|
+| free_speech    | 0.98     | 90         | 6        |
+| keywords       | 0.05     | 6          | 2        |
+| monologues     | 0.70     | 45         | 9        |
+
+## File Structure
+```
+data/
+    english_china/
+        train-0000.parquet
+    english_nigeria/
+        train-0000.parquet
+    english_united_states/
+        train-0000.parquet
+    german_germany/
+        train-0000.parquet
+    spanish_mexico/
+        train-0000.parquet
+```
+
+Each parquet contains a mixture of **free_speech**, **keywords**, and **monologues**.
+
+## Feature Schema
+All configurations share the same feature structure:
+
+- id: integer (unique identifier)
+- speaker_id: string (hashed or anonymized speaker ID)
+- gender: string (speaker gender)
+- ethnicity: string (speaker ethnicity)
+- occupation: float (occupation or profession, stored as float per original schema)
+- country_code: string (ISO 3166-1 alpha-2 code)
+- birth_place: string (country or region of birth)
+- mother_tongue: string (native language)
+- dialect: string (regional dialect)
+- year_of_birth: int (birth year, YYYY)
+- years_at_birth_place: int (years lived at birth place)
+- languages_data: string (serialized language–proficiency data)
+- os: string (recording operating system)
+- device: string (recording device type)
+- browser: string (browser used if web-based)
+- duration: float (seconds) (audio length)
+- emotions: string (brace-formatted emotion labels)
+- language: string (primary language of the recording)
+- location: string (recording location category)
+- noise_sources: string (brace-formatted background noise labels)
+- script_id: int (script template identifier)
+- type_of_script: string {free_speech, keywords, monologues} (script category)
+- script: string (text intended to be spoken)
+- transcript: string (Whisper-generated transcription)
+- transcription_segments: string (serialized segmentation with timing and word data)
+- audio: WAV audio object (associated audio file)
+
+## Licensing
+Released under **CC BY-NC 4.0**.  
+Commercial use is not permitted. Attribution to **Silencio Network** is required for any publication or derivative dataset.
+
+## Intended Use
+Suitable for:
+
+- accent-conditioned ASR training  
+- multilingual speech recognition  
+- TTS voicebank generation  
+- speaker embedding and similarity evaluation  
+- robustness benchmarking  
+- keyword-spotting models  
+- segmentation and VAD evaluation
+
+## Limitations
+- Transcripts are automatically generated. Errors may be present.  
+- Crowdsourced device diversity introduces variable noise levels.  
+
+## Citation
+```
+@dataset{silencio_network_speech_2025,
+    title        = {Silencio Network Multilingual Accent Speech Corpus},
+    author       = {Silencio Network},
+    year         = {2025},
+    license      = {CC BY-NC 4.0}
+}
+```