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filler@godaddy.com
AI is utilising Large Language Models with NLP to make machine interaction feel human in text based conversations. Using speech input is only as good as the recognition accuracy. Combinations of languages and accent pronunciation, makes a more nuanced representation than standard models allow. So, if we need accuracy on recognising words and phrases that are outside of the training of a model, a more human like recognition is required. This is the unique FlexSR approach.
Speech is the most challenging of the unstructured communication types, with different domain lexicons, languages and accents. Conventional ASR requires an acoustic model and the skill set to train for each and every combination. FlexSR can be applied without models. Saving massive costs and time to market for your integrated solutions. Important for Contact Centres Agent Monitoring, Legal Discovery, Financial Markets Compliance Communications Surveillance, Pricing and Order Entry Systems
This is a mature area for ASR with vendors adding richness to the experience with cloud services. Without cloud, the commands for control are limited. Language and accents restrict the recognition ability that can be run on the onboard compute. FlexSR is not restricted to any combination of lexicons, language and accents in recognising speech on restricted compute resources. This can unlock capabilities not previously considered as viable.
Historically transcription relied on humans. More recently ASR is being applied to give a text output to speech and augmented by a human to fix mistakes made by the ASR, which needs a model built for every combination of languages and accent pronunciations. This is a hugely timely and expert process, making cost high and time to market long. FlexSR enables any combination of language, lexicons and pronunciations to be used without model building or expertise. In addition, FlexSR can be used to check your transcription service output against the audio for correct phonological features
Speech to Text is not new to mobile phone providers. They have rich services when connected to cloud services, but somewhat restricted when limited to on-board resources. FlexSR removes such restrictions and can hold any lexicons in any language described in the International Phonetic Alphabet and match the spoken words and phrases. It has a special ability to learn a speakers accent too, and able to apply that to the word matching to improve accuracy. This opens up the mobile to a larger array of applications that rely on accurate speech recognition, that can be easily applied and without using huge compute resource.
FlexSR can identify the linguist phonological variance in a speaker's pronunciation of words. It can offer a critique and advice on how the sounds should be pronounced and positioning of the tongue, lips, nasal work, vocal chords etc, This can form the basis for developers of Language Learning solutions. It does not need acoustic models to be built for each language as it can use IPA described lexicons. This removes the need for specialist model training and expertise and enables rapid time to market for language solutions.