Automated speech recognition can help CX vendors to level up their game

Automated speech recognition in call centers is delivering exceptional value

Regardless of its computer, smartphone or digital assistant devices, customers today have accepted the utilization of speech recognition when looking for basic, speedy and direct approaches to achieve an errand or access data. They expect no less when connecting with your contact center.

Because of the demand for quality customer assistance, users continue utilizing voice and human-to-human communication to guarantee exact, customized caller experiences. Study in 2019 found that 91% of respondents think increasing investment in contact centre compliance software ought to be viewed as a need in the following years.

Call centers are as yet catching billions of calls and interactions with users at different points in the call life cycle. The ascent in AI and machine learning takes call and speech monitoring to the next level. High performance automated speech recognition (ASR) can change speech-to-text as well as empower call centers to change themselves into big data analysis hubs, providing huge amounts of learning and insight.

Automated speech recognition by machine has been a field of research for over 60 years. The sector has built up an expansive scope of business products where ASR as UI has become perpetually valuable and inescapable. Consumer-centric applications progressively require ASR to be powerful to the full range of real-world noise and other acoustic mutilating conditions. Notwithstanding, reliably recognizing spoken words in practical acoustic conditions is as yet a challenge.

For example, Sharpen, a seller of a cloud-based contact center platform, offers an automated transcription service as an additional feature in its product package. Sharpen previously got familiar with Deepgram a couple of years back, in the wake of seeing it exhibit its automated speech recognition platform at a conference.

The platform is based on deep learning models and can come pre-trained on Deepgram's library of calls. Customers can upload pre-named speech files or label speech as they go, to additional training and make the platform as tailor-made. Customers can run the platform in the cloud or on-premises and can get to the speech recognition models through APIs.

In compliance guidelines, ASR can be utilized to find explicit discussions and keywords for a scope of situations, for example, adherence to guidelines, quality management, event reconstruction and dispute resolution. The implications for failing to comply are immense – including high punishments, harmed reputation and legal action.

Team leaders in call centers can use ASR to more readily comprehend the quality of their group's calls . By being able to take an undeniable level strategic perspective on call data, they can provide suitable training, nurturing teams dependent on information and assessing scripted answers to all the more likely oversee quality control. Financial organizations are progressively utilizing AI systems too. ASR is utilized for autonomously transcribing and analysing financial calls for everything from furious customer complaints to unlawful behavior.

Sharpen's clients utilize the automated transcription service. Since it's free to them, many use it since they can, in any case, the record will be beneficial to them in the future. Numerous likewise depend on the platform for targeted utilization, including distinguishing robocalls by guiding the platform to choose certain words or expressions normally utilized by robocallers and instructing sales staff.

Deepgram currently bolsters around ten languages and has recently started to upheld a real-time transcription. Multi-language uphold, specifically, will help Sharpen scale out to different nations and populations, possibly empowering them to grow quickly.