Siri Wake Words and Voice Commands in US English
Project Overview:
Objective
Our goal was to develop an extensive dataset of audio clips featuring the “Hey Siri” wake word and various voice commands in US English. This dataset was specifically curated to improve the functionality of voice recognition systems and voice assistants, particularly for Apple’s Siri technology.
Scope
We successfully collected a wide range of audio recordings from native US English speakers, featuring different accents and in diverse contexts. Each recording was meticulously annotated to include precise wake word and voice command details.
Sources
- Voice Assistant Users: Collaborate with Siri users who consent to contribute audio clips of them saying “Hey Siri” followed by voice commands in different contexts.
- Voice Actors: Hire professional voice actors to create synthetic wake word and voice command recordings for added diversity and control.
- Public Domain Recordings: Extract publicly available audio recordings with instances of the “Hey Siri” wake word and voice commands in US English.
Data Collection Metrics
- Total Audio Clips Collected and Annotated: 150,000 clips (Randomly added volume)
- User Contributions: 75,000
- Voice Actor Recordings: 40,000
- Public Domain Extracts: 35,000
Annotation Process
Stages
- Wake Word and Command Annotation: We accurately identified and marked the “Hey Siri” wake words and the subsequent voice commands within each audio clip.
- Speaker Demographics: We gathered metadata on the speakers, including age, accent, and gender.
- Recording Conditions: We documented the recording conditions, such as background noise levels and acoustic environments.
Annotation Metrics
- Audio Clips with Wake Word and Command Annotations: 100,000
- Speaker Demographic Metadata: 100,000
- Recording Condition Metadata: 100,000
Quality Assurance
Stages
Annotation Verification: A comprehensive validation using automated tools and human reviewers to ensure accurate annotations.
User Consent: We guaranteed that all user-contributed audio clips were obtained with explicit consent and anonymized to protect personal information.
Privacy Compliance: Adherence to privacy regulations, including data retention policies and the right to be forgotten.
QA Metrics
- Annotation Validation Cases: 10,000 (10% of total)
- Privacy Audits: 60,000 (for user-contributed data)
Conclusion
This project significantly advances voice recognition technology, especially for Apple’s Siri. Our dataset stands out due to its diversity, precise annotations, and compliance with privacy standards, making it an invaluable resource for research and development in voice recognition and natural language processing.
Quality Data Creation
Guaranteed TAT
ISO 9001:2015, ISO/IEC 27001:2013 Certified
HIPAA Compliance
GDPR Compliance
Compliance and Security
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