Deploying DanSpeech models instead of using an external API will, in addition to reducing costs, also reduce latency drastically, if deployed locally with a GPU. Systems, or companies who simply do not wish to outsource this part of their pipeline. With a desire to utilize speech recognition in the development of Danish technologies might be hindered by cost barriers.Īs such DanSpeech can be used commercially by companies without the resources to develop their own speech recognition And without an easy-to-use, and free system, innovative spirits Speech recognition will inevitably be a big part of future IT innovations. Systems are not continually out-shined by English systems. We believe that an open-source solution can play an important role in ensuring that Danish speech recognition Therefore we decided to developĪn open-source, and easy-to-use automatic speech recognition system for Danish. We believe that speech recognition in Danish should be freely available for everyone to use. Pre-trained models of varying sizes and complexities. Text-to-speech is a powerful technology that can help bridge the gap between humans and machines by enabling machines to speak and understand human language. Not perfect, and results are conditioned on specific use-cases.Īn easy-to-use Recognizer that supports different use-cases for Danish speech recognition. With the rise of the new AI models like GPT-4, being able to communicate with machines in a natural and intuitive way is becoming more and more important. While DanSpeech models perform state-of-the-art speech recognition in Danish, performance is To achieve the best results, DanSpeech provides language models trained on a large danish corpus as part of the released package. The models may be combined with a language model through beam-search decoding The models are trained with various data agumentations to multiply the rather small amount of public speech recognition It was developed as part of a Master’s thesis at DTU computeīy Martin Carsten Nielsen and Rasmus Arpe Fogh Jensen, supervised by Professor Lars Kai Hansen.Īll DanSpeech models are end-to-end DeepSpeech 2 models, trained on danish data with a CTC loss. DanSpeech is an open-source Danish speech recognition (speech-to-text) python package based on the
0 Comments
Leave a Reply. |