You will then move on to building neural networks that can map these audio features to transcribed text. After learning about the basic types of layers that are often used for deep learning-based ...

The model provided in this example corresponds to the pretrained Deep Speech model provided by [2]. The model was trained using the Fisher, LibriSpeech, Switchboard, and Common Voice English datasets, ...

In this study, we have used pretrained word embedding approaches such as word2vec and fast text, and assessed their effectiveness for hateful speech recognition and classification in Afaan Oromo text ...

In short text classification, extracting text features is crucial. Static word vector training, the traditional method, has limitations such as insufficient semantics and sparse features, while ...

What is natural language processing? Natural language processing, or NLP, is currently one of the major successful application areas for deep learning, despite stories about its failures.

Bark is a universal text-to-audio model that can not only create realistic speech, it can incorporate music, background noises, and sound effects. It can even include non-speech sounds like laughte… ...

Text to speech (TTS) has attracted a lot of attention recently due to advancements in deep learning. Neural network-based TTS models (such as Tacotron 2, DeepVoice 3 and Transformer TTS) have ...

The company took a step in another technological direction by launching its first stand-alone speech-to-text model called Scribe.