Alexa Wake Words in Italian (Youth)

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Project Overview:

Objective

As a leading data collection and annotation firm, we successfully completed a project aimed at constructing a comprehensive dataset of audio clips featuring the “Alexa” wake word, articulated in Italian by young speakers. This dataset is a crucial component in advancing wake word detection technologies and voice assistant systems tailored for Italian-speaking youth.

Scope

Our project encompassed the acquisition of a wide array of audio recordings from Italian-speaking youth across diverse environments and accents. Each recording was meticulously annotated with precise wakeword details.

Sources

Youth Contributors: We engaged with young individuals willing to provide audio clips of the “Alexa” wake word in various Italian contexts.
Youth Voice Actors: We employed young, Italian-fluent voice actors to generate synthetic wake word recordings, enhancing the dataset’s diversity and relevance.
Public Domain Recordings: We incorporated publicly available audio recordings featuring the “Alexa” wake word in Italian, enriching our dataset.

Data Collection Metrics

Total Audio Clips Collected: 25,000
Youth Contributor Recordings: 15,000
Youth Voice Actor Recordings: 7,500
Public Domain Extracts: 2,500 (subject to availability)
Random Volume Addition: Additional 3,000 clips, enhancing the dataset’s robustness.

Annotation Process

Stages

Wake Word Annotation: We marked the exact moments of the “Alexa” wake word in each audio clip.
Contributor Demographics: Information regarding the age, accent, and gender of youth contributors was systematically collected.
Recording Conditions: We documented various recording conditions, including ambient noise levels and the devices used.

Annotation Metrics

Audio Clips with Wake Word Annotations: 25,000
Contributor Demographics: 25,000
Recording Condition Metadata: 25,000

Quality Assurance

Stages

Annotation Verification: Our process included both automated tools and youth reviewers to ensure accurate wake word annotations.
Youth and Parental Consent: We ensured all youth-contributed audio clips had explicit consent, with parental permission secured where necessary. Any personally identifiable information was anonymized
Privacy Compliance: We strictly adhered to privacy regulations, enabling youth contributors or their guardians to opt-out or request data removal at any time.

QA Metrics

Annotation Validation Cases: 2,500 (10% of total)
Privacy Audits: 15,000 (specifically for youth-contributed data)

Conclusion

The Alexa Wake Words Dataset in Italian (Youth) project, spearheaded by our company, serves as a testament to our expertise in creating specialized datasets. This project not only enhances wake word detection for the Italian-speaking youth but also demonstrates our commitment to privacy, quality, and comprehensive data annotation services. Our diverse dataset stands as a valuable asset for research and development in voice recognition and natural language processing.