OPUS to HTK Converter

Generate HTK speech processing audio from OPUS

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ASR Training Format

HTK is standard for HMM speech recognition — convert OPUS speech recordings for research pipelines.

Corpus Processing

Upload entire OPUS speech datasets and produce HTK-formatted audio for every file at once.

Online Conversion

No HTK toolkit installation needed — produce formatted audio from OPUS in your browser.

How to convert OPUS to HTK

1

Select files from Computer, Google Drive, Dropbox, URL or by dragging it on the page.

2

Choose htk or any other format you need as a result (more than 200 formats supported)

3

Let the file convert and you can download your htk file right afterwards

About formats

Opus is a versatile, open audio codec standardized by the IETF as RFC 6716 in 2012. It fuses two coding approaches — SILK for speech and CELT for music — into one algorithm that blends between them based on content type and bitrate. This hybrid design lets Opus outperform virtually every other codec across a wide range of uses: low-latency voice at 6 kbps, high-fidelity music at 128 kbps, and everything in between. It supports bitrates from 6 to 510 kbps, sample rates up to 48 kHz, and frame sizes as small as 2.5 ms, giving it the lowest algorithmic latency of any mainstream audio codec. Three advantages make Opus especially compelling. It is completely royalty-free and open-source, removing licensing barriers that hold back proprietary codecs. It achieves transparent quality at roughly half the bitrate of MP3 and beats AAC at equivalent rates. And its low latency makes it the mandatory codec for WebRTC, so every modern browser ships with an Opus decoder. WhatsApp, Discord, Zoom, and YouTube all rely on Opus for real-time audio.
Initial release: September 11, 2012
HTK is the native waveform container for the Hidden Markov Model Toolkit, a software suite developed at Cambridge University's Engineering Department for speech recognition research. First distributed in 1993, HTK rapidly became a reference platform in computational linguistics labs worldwide, and its file format followed suit. Each file stores a sequence of parameter vectors or raw samples prefixed by a 12-byte header specifying the number of frames, the frame period in 100 ns units, the byte count per frame, and a type code indicating the data kind — options range from waveform PCM to Mel-frequency cepstral coefficients and filter-bank energies. This versatility lets a single container carry both source audio and extracted features without changing parsers. The deliberately minimal header avoids alignment padding or optional chunks, making the format trivial to read from C, Python, or MATLAB with a few lines of binary I/O. Three advantages underpin HTK's lasting relevance: tight integration with the HTK training and recognition pipeline, deterministic byte layout that eliminates parser ambiguity, and widespread adoption in academic corpora.
Initial release: 1993

Frequently Asked Questions

Why convert OPUS to HTK?

HTK format is required by the Hidden Markov Model Toolkit for ASR training. Speech researchers need HTK-formatted input data.

What uses HTK?

The Cambridge HTK toolkit, Kaldi, and speech recognition research pipelines consume HTK-formatted audio.

Is HTK common?

HTK is specialized for speech processing research — a 16-bit PCM format with custom headers, not general-purpose audio.

What sample rate?

Most ASR tasks use 8 or 16 kHz mono — the converter handles resampling from OPUS automatically.

Can I convert a dataset?

Upload an entire OPUS speech corpus and convert it to HTK in one batch — ready for model training.