Hinglish Code-Switched Conversational Dataset v1
Overview
This dataset contains structured Hinglish conversational voice data built to reflect how people actually speak in real-world interactions.
Most speech datasets are clean, scripted, or heavily processed. That works in controlled testing, but it breaks in production where speakers interrupt each other, switch languages, use regional accents, pause mid-thought, and shift context naturally.
This sample release demonstrates Sonexis’ structured approach to conversational voice data.
What This Dataset Contains
Each conversation includes:
- speaker-separated audio
- structured transcripts
- conversation-level metadata
- speaker-level metadata
- code-switching indicators
- conversational annotations
- scenario-level context
The dataset is designed for teams building or evaluating multilingual voice AI systems for India and other multilingual markets.
Languages
This release focuses on Hinglish, with natural switching between:
- Hindi
- English
The conversations may include informal speech, regional accent variation, interruptions, overlaps, and context shifts.
Dataset Structure
audio/
conversation_0001/
conversation_0001_spk1_16k.wav
conversation_0001_spk2_16k.wav
conversation_0002/
conversation_0002_spk1_16k.wav
conversation_0002_spk2_16k.wav
transcripts/
conversation_0001.json
conversation_0002.json
annotations/
conversation_0001.json
conversation_0002.json
manifests/
conversations.jsonl
speakers.jsonl
speaker_separated.jsonl
utterances.jsonl
final_transcripts.jsonl
metadata.jsonl
conversation_metadata.json
docs/
dataset_schema.json
schema.md
- Downloads last month
- 35