What components are included in a wake word dataset?

A wake word dataset from FutureBeeAI includes:

1. Wake word audio samples
2. Follow-up command phrases
3. Diverse speaker and environment recordings
4. High-quality WAV files, transcripts, and rich metadata
5. QA-verified annotations

This comprehensive structure ensures our datasets are robust and ready to enhance the performance of voice-activated AI technologies.

Wake Words + Command Phrases

Our datasets feature comprehensive audio collections of primary wake words like “Alexa,” “Hey Siri,” and “OK Google,” as well as brand-specific and device-specific triggers such as “Bixby” and “LG Smart.” Additionally, they include command phrases that follow wake words (e.g., “Hey Google, play music”) and standalone commands (e.g., “Turn on lights”).

Audio Standards & File Structure

We maintain strict standards for audio quality, providing files in 16 kHz, 16-bit, mono WAV format. Each dataset is paired with detailed transcription files in TXT or JSON formats, and a comprehensive metadata schema that captures speaker demographics, language, and recording environment.

Diverse Speaker & Environment Recordings

Our datasets ensure diversity by including recordings from a broad range of speakers across different accents, age groups, and genders. These recordings are made in various noise-controlled environments, simulating real-world conditions and enhancing model robustness.

Pre-processing & Annotation

Before inclusion, audio is subjected to:

• Noise filtering
• Normalization
• Silence trimming

Transcripts are annotated with phoneme-level alignment and timestamped segments, ensuring precise accuracy. Our in-house QA workflow validates these through a 2-layer review system, maintaining audio quality with less than 1% Word Error Rate (WER).

Data Augmentation & Balance

To bolster model robustness, we apply data augmentation techniques such as synthetic noise injection and speed/pitch variation. We also enforce balanced speaker quotas, ensuring representation across different demographics for enhanced model generalization.

Compliance & Privacy

All recordings comply with privacy regulations such as GDPR and CCPA. We manage consent meticulously and remove any personally identifiable information (PII), ensuring the integrity and security of our datasets.

Performance Metrics & Dataset Volume

Our internal QA ensures metadata accuracy exceeds 99%. Each Off-the-Shelf (OTS) dataset contains approximately 1,000–5,000 utterances per wake word, collected across more than 10 different environments, catering to multilingual needs.

Real-World Applications & Use Cases

FutureBeeAI's wake word datasets are vital for various applications, including smart home devices, automotive voice assistants, and mobile applications. These datasets drive high accuracy and efficiency in voice-activated systems, enhancing user experiences across industries.

FutureBeeAI: Your Partner in Voice AI

At FutureBeeAI, we provide both OTS and custom datasets through our proprietary YUGO speech data collection platform, ensuring structured and scalable data solutions. Whether you're dealing with specific wake words or require multilingual datasets, our offerings are designed to meet your AI goals efficiently.

By investing in our high-quality wake word datasets, you can elevate your voice AI solutions to new heights. Let FutureBeeAI support your journey with our comprehensive, scalable data solutions.

Mini FAQ

Q. What file formats are provided?

A: 16 kHz WAV + TXT/JSON transcripts.

Q. How do you ensure diversity?

A: Balanced quotas across accents, age, gender, and environments.

Q. How is metadata structured?

A: Detailed schema including speaker demographics and recording context.