Voice Data Collection for AI Engines and Transcription – Case Study
About the Client
The case study is about data collection for AI and transcription. The client is a global leader in AI. With a commitment to innovation and customer satisfaction, the client aims to enhance user experience through advanced voice recognition technologies that cater to diverse linguistic demographics.
Client Requirements
The client aimed to train their AI-powered voice assistant for voice command recognition in various local languages. The objective was to create a robust dataset that would enable the AI-powered voice assistant to understand and process voice commands accurately across different demographics, including variations in age, gender, education and regional dialects. The project required the collection of 1,000 hours of audio data for each language, with recordings from individuals representing a wide range of backgrounds. Each participant was expected to provide between 30 minutes to 1 hour of conversational audio.
The client highlighted the need for high-quality, conversational-type audio recorded in two separate channels, as per stringent technical specifications, to facilitate better training of the AI models.
Project Details – Data Collection for AI and Transcription
Service:
Data Collection & Transcription for AI-powered voice assistant
Languages Covered:
Marathi, Hindi, Gujarati, Bengali, Tamil, Telugu, Kannada, Malayalam, Punjabi, Odia, Urdu, Simplified Chinese, Taiwanese Chinese, Korean, Singaporean English, Thai, Indonesian, Japanese, English
Duration:
8 months to 1 year
Challenges Faced:
The project presented several challenges that needed to be addressed to meet the client’s requirements effectively:
Diverse Demographics
Collecting audio samples from a wide range of demographics posed logistical challenges, including identifying suitable participants across various regions and ensuring representation in terms of age, gender and education.
Quality Control
Ensuring the quality of the audio recordings was critical. The recordings needed to be clear and representative of natural conversational speech.
Volume of Data
The requirement for 500-1,000 hours of audio data for each language required extensive planning and coordination to manage the recording sessions efficiently.
Technical Specifications
The client specified that audio should be recorded in two separate channels in a conversational format for each participant, which required careful setup and monitoring during the recording process.
Solutions Provided for Audio Data Collection Services
Fidel implemented an end-to-end strategy to address the client’s requirements and challenges:
Establishment of Recording Centers
Fidel established multiple recording centers across various regions to enable the collection of audio samples. These centers were strategically located to ensure access to diverse demographic groups.
Participant Recruitment
A wide-ranging audience was targeted for participant recruitment. Fidel operated various outreach methods to ensure a representative sample of the population.
Audio Recording Process
The audio data was recorded in two channels to capture natural conversational exchanges. Each session was designed to be interactive, allowing participants to engage in dialogue rather than delivering monologues. This approach ensured that the recordings reflected real-life conversational dynamics.
Automated Transcription QC Tools
Developed a custom transcription tools to automate quality checks on active transcribed and batch of files. Integrated an automated quality control mechanism to detect and correct discrepancies in transcriptions. Calculates no-speech duration. Identifies missing punctuations from speech contents. Identifies incorrect abbreviated contents. Enabled efficient timestamp alignment to enhance accuracy and usability of the transcribed data.
Quality Assurance
After the recordings were completed, a rigorous quality control process was implemented. Each audio file was reviewed for clarity and adherence to the client’s specifications. Only recordings that met the high standards set by the client were forwarded for transcription.
Transcription and Delivery
Following client approval of the recorded audio, we provided transcription services with timestamps. The final deliverables included both the audio files and their corresponding transcriptions, ensuring that the client received a comprehensive dataset for AI training.
Results
The project was successfully completed within the stipulated timeframe of 8 months to 1 year, delivering high-quality audio data that met the client’s specifications. The key benefits of the project included:
1. Diverse Dataset:
The client received a huge dataset that accurately represented various demographics, enhancing the AI’s ability to understand and process voice commands in multiple languages.
2. High-Quality Audio:
The two-channel recordings captured natural conversational speech, providing the AI with realistic training data that improved its performance in real-world applications.
3. Efficient Process:
The structured approach to participant recruitment, recording and quality control ensured that the project was completed on time.
4. Enhanced AI Capabilities:
With the newly trained AI engines, the client was able to improve user experience across their platforms, leading to increased customer satisfaction and engagement.
Connect with Fidel for Voice Data Collection and AI Audio Transcription Services
Fidel specializes in high-quality data collection and transcription services to support AI-driven applications. If you’re looking for multilingual datasets to enhance your AI models, reach out to us today at sales@fidelsoftech.com.