WMA to HTK Converter

Generate HTK speech processing audio from WMA

Drop files here. 1 GB maximum file size or Sign Up
to
Facebook Amazon Microsoft Tesla Nestle Walmart L'Oreal

ASR Training Format

HTK is standard for speech recognition — convert WMA recordings for research.

Corpus Processing

Upload entire WMA datasets and produce HTK audio for every file.

Online Conversion

No HTK toolkit needed — convert WMA to HTK in your browser.

How to convert WMA 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

WMA (Windows Media Audio) is a family of proprietary audio codecs developed by Microsoft and first released in 1999 as part of the Windows Media framework. Created to compete with MP3 and AAC, WMA Standard uses perceptual coding to deliver what Microsoft claimed was near-CD quality at bitrates as low as 64 kbps — roughly half the data rate MP3 typically needed for comparable results. The codec family grew to include WMA Professional for surround sound and high-resolution audio, WMA Lossless for bit-perfect archival compression, and WMA Voice optimized for spoken content at very low bitrates. Deep integration with Windows, Windows Media Player, and the Zune ecosystem gave WMA a strong distribution advantage throughout the 2000s, and digital rights management (DRM) support made it attractive to online music stores of that era. Encoding and decoding are handled natively by Windows, requiring no third-party software for playback on any Windows machine. Cross-platform support has improved through libraries like FFmpeg and GStreamer, though WMA remains less universally compatible than MP3 or AAC on non-Microsoft devices. The format still appears in legacy media libraries, though newer codecs have largely taken its place for streaming and portable use.
Initial release: 1999
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 WMA to HTK?

HTK format is required for HMM speech recognition training. The HTK toolkit cannot consume WMA directly.

What uses HTK?

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

Does format matter for ASR?

Yes — HTK tools require specific PCM format with custom headers for model training.

What sample rate?

Most ASR tasks use 8 or 16 kHz mono — resampled automatically from WMA.

Can I convert a dataset?

Upload an entire WMA speech corpus and convert to HTK in one batch.