Speechmatics launches Global English, an accent-agnostic language pack for speech-to-text transcription

When tested against providers of similar solutions, GE consistently produced more accurate transcriptions. Compared directly, GE was between 3% and 55% more accurate than all Google’s Cloud Speech API accent-specific language packs and between 5% and 23% more accurate than IBM’s Cloud US English language pack*.

It supports every major English accent providing a consistent and cost-effective solution Today, Speechmatics is announcing the launch of Global English, a single English language pack supporting all major English accents for use in speech-to-text transcription. Global English (GE) was trained on thousands of hours of spoken data from over 40 countries and tens of billions of words drawn from global sources, making it one of the most comprehensive and accurate accent-agnostic transcription solutions on the market.

Traditionally, speech recognition has dealt with variations in language by producing a different language pack for every distinct accent or region. However, this meant a whole new set of models trained on data from that particular subset of speakers of the languages. With the launch of GE, Speechmatics is aiming to democratise speech-to-text transcription to overcome industry-wide issues where there are multiple English accents in one recording. Thus, providing a far more accurate, consistent and cost-effective solution. Speech recognition has advanced hugely in recent years, making GE possible. The team has been gathering data from a wide range of sources and taking advantage of the astonishing rise in computer power, allowing them to train bigger models, based on more data, capable of supporting more variations. Speechmatics has now built 72 unique languages, more than any other provider on the market, including Amazon, Google, Nuance, Microsoft and IBM. With the modern neural network architectures capable of generalising across variations in speech by using representation learning, Speechmatics were able to generate the accuracy of multiple specialised models all in one language pack.