Hinglish media Audio Dataset

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Project Overview:

Objective

The “Hinglish Media Audio Dataset” project is designed to create a comprehensive audio dataset that combines Hindi and English languages (Hinglish) for advanced speech recognition applications. This dataset is pivotal for training AI models in understanding and processing mixed-language speech, which is commonly used in various regions, particularly in India.

Scope

Diverse Environmental Conditions: The dataset includes recordings from a range of environments, from quiet indoor settings to noisy outdoor locations, which helps in training models to accurately process speech under various acoustic conditions.
Variety of Speech Contexts: Capturing Hinglish speech in different contexts such as informal conversations, media broadcasts, public speeches, and digital communications, ensuring the models can generalize across different speech situations.

Sources

Audio samples were sourced from a mix of national and regional media outlets, ensuring a representation of both mainstream and niche content.
Collaborations with broadcasters and digital platforms were key in acquiring a comprehensive range of Hinglish audio material.
The collected data successfully generated a diverse and authentic set of Hinglish audio interactions, capturing the nuances of language and cultural expression.

Data Collection Metrics

Total Hinglish Recordings: 22,500
Volunteers’ Contributions: 15,000
Public Domain Datasets: 4,500
Professional Recordings: 3,000

Annotation Process

Stages

Language Identification: Labeling each recording with predominant language indicators (Hindi, English, or Mixed).
Metadata Documentation: Recording details like the date, time, and context of each speech sample.

Annotation Metrics

Recordings with Language Labels: 22,500
Metadata Entries: 22,500

Quality Assurance

Stages

Annotation Review: Expert linguists review the labels for accuracy and consistency.
Data Integrity Checks: Filtering out recordings that don’t meet the quality standards.
Data Security: Upholding privacy norms and ensuring data confidentiality.

QA Metrics

Reviewed Annotations: 2,250 (10% of total)
Data Cleansing: Exclusion of inadequate recordings

Conclusion

The “Hinglish Media Audio Dataset” represents a significant stride in the realm of speech recognition technology. By offering a rich and diverse range of Hinglish audio samples, accurately annotated and quality-assured, this dataset lays the groundwork for sophisticated AI systems capable of understanding and processing mixed-language speech. It’s a step forward in bridging linguistic diversity, particularly beneficial for regions where Hinglish is a prevalent mode of communication.