Alexa Wake Words in EU Spanish (Youth)
Project Overview:
Objective
As a leading data collection and annotation company, we specialize in providing diverse datasets, including images, videos, text, and speech, to train sophisticated machine learning models. This case study highlights our successful project in collecting and annotating a substantial dataset of EU Spanish youth voice recordings, specifically for improving the responsiveness of Alexa wake words.
Scope
Our objective was to gather and annotate a large volume of EU Spanish youth voice recordings. Small businesses and startups need to get strategic with their limited marketing budgets. We really honed in on getting a wide variety of accents, dialects, and ways young Europeans speaking Spanish express themselves.
Sources
- Participants: Collaborate with EU Spanish-speaking youth who consent to contribute audio clips of them saying “Alexa” in different contexts.
- Voice Actors: Hire professional voice actors fluent in EU Spanish to create synthetic wake word recordings for added diversity and control.
Data Collection Metrics
- Total Data Collected: 150,000 voice recordings
- Total Data Annotated: 120,000 voice recordings
- Age Group: 10-18 years
- Geographic Focus: Spain and EU Spanish-speaking regions
- Duration: 6 months
Annotation Process
Stages
- Wake Word Annotation: Accurately mark the temporal boundaries of the “Alexa” wake word within each audio clip.
- Participant Demographics: Gather metadata about participants, including age, accent, and gender
- Recording Conditions: Document recording conditions such as ambient noise levels and recording devices used.
Annotation Metrics
- Audio Clips with Wake Word Annotations: 15,000
- Participant Demographic Metadata: 15,000
- Recording Condition Metadata: 15,000
Quality Assurance
Stages
Annotation Verification: Implement a robust validation process involving automated verification tools and human reviewers to ensure precise wake word annotations.
User Consent: Ensure that participants’ audio clips have explicit consent for usage in the dataset and anonymize any personally identifiable information.
Privacy Compliance: Adhere to privacy regulations, including data protection policies and mechanisms for participants to opt out or request data removal.
QA Metrics
- Annotation Validation Cases: 1,500 (10% of total)
- Privacy Audits: 9,000 (for participant-contributed data)
Conclusion
This project exemplifies our capability in handling large-scale data collection and annotation tasks with precision and efficiency. With our knack for crafting custom datasets for machine learning, we’re a top pick when it comes to similar future projects.
Quality Data Creation
Guaranteed TAT
ISO 9001:2015, ISO/IEC 27001:2013 Certified
HIPAA Compliance
GDPR Compliance
Compliance and Security
Let's Discuss your Data collection Requirement With Us
To get a detailed estimation of requirements please reach us.