Kannada TTS Dataset for Speech Synthesis

Professionally recorded Kannada speech dataset featuring monologue-style readings by native speakers. Paired with clean transcripts and rich metadata, this dataset is ideal for training text-to-speech systems and voice synthesis models.

About this Off-the-shelf Speech Dataset

The Kannada TTS Monologue Speech Dataset is a professionally curated resource built to train realistic, expressive, and production-grade text-to-speech (TTS) systems. It contains studio-recorded long-form speech by trained native Kannada voice artists, each contributing 1 to 2 hours of clean, uninterrupted monologue audio.

Unlike typical prompt-based datasets with short, isolated phrases, this collection features long-form, topic-driven monologues that mirror natural human narration. It includes content types that are directly useful for real-world applications, like audiobook-style storytelling, educational lectures, health advisories, product explainers, digital how-tos, formal announcements, and more.

All recordings are captured in professional studios using high-end equipment and under the guidance of experienced voice directors.

Recording & Audio Quality

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Audio Format: WAV, 48 kHz, available in 16-bit, 24-bit, and 32-bit depth

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SNR: Minimum 30 dB

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Channel: Mono

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Recording Duration: 20-30 minutes

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Recording Environment: Studio-controlled, acoustically treated rooms

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Per Speaker Volume: 1–2 hours of speech per artist

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Quality Control: Each file is reviewed and cleaned for common acoustic issues, including: reverberation, lip smacks, mouth clicks, thumping, hissing, plosives, sibilance, background noise, static interference, clipping, and other artifacts.

Only clean, production-grade audio makes it into the final dataset.

Voice Artist Selection

All voice artists are native Kannada speakers with professional training or prior experience in narration. We ensure a diverse pool in terms of age, gender, and region to bring a balanced and rich vocal dataset.

•Artist Profile:

•Gender: Male and Female

•Age Range: 20–60 years

•Regions: Native Kannada-speaking states from Karnataka

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Selection Process: All artists are screened, onboarded, and sample-approved using FutureBeeAI’s proprietary Yugo platform.

Script Quality & Coverage

Scripts are not generic or repetitive. Scripts are professionally authored by domain experts to reflect real-world use cases. They avoid redundancy and include modern vocabulary, emotional range, and phonetically rich sentence structures.

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Word Count per Script: 3,000–5,000 words per 30-minute session

•Content Types:

•Storytelling

•Script and book reading

•Informational explainers

•Government service instructions

•E-commerce tutorials

•Motivational content

•Health & wellness guides

•Education & career advice

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Linguistic Design: Balanced punctuation, emotional range, modern syntax, and vocabulary diversity

Transcripts & Alignment

While the script is used during the recording, we also provide post-recording updates to ensure the transcript reflects the final spoken audio. Minor edits are made to adjust for skipped or rephrased words.

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Segmentation: Time-stamped at the sentence level, aligned to actual spoken delivery

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Format: Available in plain text and JSON

•Post-processing:

•Corrected for disfluencies

•Matched to actual spoken audio

•Quality checked by a native language expert

Metadata

Every recording and speaker is tagged with detailed metadata. This metadata enables filtering, speaker-level analysis, and targeted fine-tuning during model training.

•Speaker Metadata:

•Gender

•Age group

•Regional background

•Recording Metadata:

•File duration

•Bit depth

•Sample rate

•Acoustic environment

•QA status

•Content Metadata:

•Domain (e.g., health, education, product guide)

•Topic

•Speaking style (neutral, formal, emotional)

Quality Assurance Process

Each recording goes through a multi-stage QA workflow:

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Pre-Recording: Voice artists are trained on script delivery, tone, and clarity

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Supervised Recording: Emotional or expressive scripts are recorded with guidance from voice directors

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Linguistic Review: Native Kannada experts review the spoken content for accuracy and delivery

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Acoustic Review: Sound engineers evaluate each file to detect and clean technical artifacts

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Final Approval: Only files that pass all checks and include complete metadata are added to the final dataset.

Dataset Limitations

This dataset is optimized for high-quality TTS training, but like any off-the-shelf resource, it’s important to be aware of a few practical boundaries:

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Per-Speaker Duration: Each speaker contributes 1–2 hours of recorded audio. This is ideal for training multi-speaker TTS models, but may not be sufficient for use cases like voice cloning or personalized synthesis. For those needs, we offer extended, per-speaker data collection on request.

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Monologue-Only Format: The recordings are structured as continuous monologues and do not include back-and-forth dialog or multi-party interaction. Clients looking to build natural conversational agents or response models may benefit from our scripted or spontaneous dialogue collections.

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Studio-Recorded Only: All speech is captured in clean, acoustically treated environments. As a result, this dataset is not suited for training models intended for noisy or real-world acoustic conditions (e.g., in-car, outdoor, public transport). For such scenarios, we support custom noisy-environment data collection.

Ethical Collection & Licensing

All contributors go through a structured onboarding process via our Yugo platform. We collect voice samples, confirm suitability, and obtain written consent before full dataset participation.

•No PII is collected or stored

•Consent forms are archived securely for every voice artist

Customization Options

Need something different? We support custom data collection projects, including:

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Conversational TTS: Dialogues between two or more speakers

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Scripted Sentence-Based Prompts: For short-form assistants and command systems

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Voice Cloning Data: Collect up to 30 hours per speaker across diverse domains (separate licensing required)

If your requirements go beyond the scope of this dataset, FutureBeeAI offers fully customizable data collection pipelines tailored to your model needs, speaker profile, and acoustic conditions.

License & Usage Rights

The Kannada TTS Monologue Speech Dataset is developed by FutureBeeAI and is available exclusively under a commercial license, designed to support a wide range of real-world applications while ensuring ethical and legal compliance.