TLK is an open source set of tools for Automatic Speech Recognition (ASR) developed at the Universitat Politècnica de València (UPV) by the transLectures-UPV Team. Among other functionalities, it features parameter estimation of hidden Markov models (HMMs) and recognition (speech, text...).

The current stable version (1.3.0) includes the following main ASR functions:

* Diagonal Gaussian mixture and Bernoulli mixture HMM acoustic models.
* Feature extraction.
* I/O of acoustic models.
* Initialisation of acoustic models.
* Parameter estimation for acoustic models, including the Baum-Welch and Viterbi algorithms.
* Acoustic model adaptation: MLLR and CMLLR features.
* Recognition using ARPA language models and self-generated acoustic models.
* Viterbi alignment.
* Incremental training of acoustic models.
* Weighted interpolation of acoustic models.
* Recognition using Hybrid DNN-HMMs.
* DNN adaptation.

And these additional usability features:

* High-level tools to facilitate the preprocessing, training and recognition of standard acoustic systems.
* A tool to directly transcribe a media file using a pre-installed system.
* Simple configuration files for training setup.
* Compressed ZIP file support.
* Internationalisation of tools and documentation.

The research leading to this toolkit has received funding under the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement nº 287755.