Siri Wake Words and Voice Commands in US English

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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.