Doteli Speech to Text: A Complete Guide
Doteli Speech to Text: Bridging the Digital Divide for a Rich Himalayan Language
Doteli (डोटेली), also known as Dotyali, is a language spoken by around 1.5 million people in the far-western region of Nepal and parts of northern India. It belongs to the Khas group of Indo-Aryan languages and is closely related to Nepali but with its own distinct phonology, vocabulary, and grammar. Despite its sizeable speaker population, Doteli has been largely absent from the digital speech technology landscape. Major AI transcription services like Google Speech-to-Text, Amazon Transcribe, and Otter.ai do not support Doteli at all. This leaves speakers and content creators without the tools to convert their spoken language into text efficiently.
Speechyou changes that. Our Doteli speech-to-text engine is built specifically for the language, trained on a diverse corpus of native speech across dialects. Whether you need to transcribe a podcast, generate subtitles for a YouTube video, or create searchable text from a recorded interview, Speechyou gives you accurate, Devanagari-script output in minutes.
Why Accurate Transcription of Doteli Matters
Doteli is not just a dialect of Nepali; it has a unique phonological system that includes:
- Retroflex stops (ट, ठ, ड, ढ, ण) that are acoustically distinct from dental stops
- Phonemic nasalisation of vowels (e.g., "हाँ" vs "हा")
- A pitch accent that can change word meaning, such as in काटो (kāṭo, 'thorn') vs काटो (kāṭo, 'stone') – the difference is tonal
- Four major dialects with significant lexical and phonetic variation
Generic ASR models trained on Nepali or Hindi fail to capture these features, leading to low accuracy. Speechyou's model is fine-tuned on Doteli data, including field recordings from rural Nepal, to handle these nuances correctly.
Use Cases for Doteli Transcription
Doteli speakers are increasingly creating digital content, but they lack tools to make that content accessible and searchable. Here are some key use cases:
- Podcasts and Radio: Local radio stations in Doteli-speaking areas can transcribe their shows for online publication, creating text archives and show notes.
- YouTube Subtitles: Doteli YouTubers can automatically generate SRT subtitles in Devanagari, improving reach and SEO.
- Education: Teachers can transcribe Doteli-language lectures for students, creating study materials and making content accessible to hearing-impaired learners.
- Oral History Preservation: Researchers working with Doteli elders can transcribe interviews, preserving folk tales, songs, and historical accounts for future generations.
- Government and NGO Work: Community meetings and public service announcements can be transcribed for record-keeping and transparency.
How Speechyou Handles Doteli's Challenges
Doteli presents several challenges for automatic speech recognition:
- Limited training data: Unlike Hindi or Nepali, there are few publicly available Doteli speech datasets. Speechyou has built its own collection by partnering with local linguists and community members.
- Dialectal variation: A Baitadeli speaker may pronounce words differently from a Dadeldhuri speaker. Our model is trained on multiple dialects and can be fine-tuned for a specific region.
- Retroflex and nasal sounds: These are often misrecognised by generic models. Speechyou uses acoustic models that pay special attention to retroflex and nasal features.
Get Started with Doteli Transcription Today
Speechyou offers a simple, web-based interface where you upload your audio or video file in Doteli, and within moments you receive a transcript in Devanagari script. You can also generate SRT or VTT subtitle files ready for use with video players. The Solo plan includes unlimited transcription minutes, so you can transcribe as much Doteli content as you need without worrying about per-minute costs.
Don't let your Doteli content remain trapped in audio. Convert it to text with Speechyou and unlock the power of searchable, shareable, accessible language. Try it now and hear the difference.







