Customers today have accepted the use of speech recognition regardless of their computer, smartphone, or digital assistant devices when searching for basic, quick, and direct approaches to accomplish an errand or access data. When connecting with your contact center, they expect no less.
Users continue to use voice and human-to-human communication to guarantee accurate, customized caller experiences because of the demand for quality customer assistance. In 2019, a study found that 91 percent of respondents believe that increasing investment in compliance software for contact centers should be seen as a need in the following years.
Call centers are currently capturing billions of calls and user interactions at various points in the life cycle of calls. Call and speech monitoring takes the rise in AI and machine learning to the next level. Automated high-performance speech recognition (ASR) can alter speech-to-text as well as empower call centers to turn into hubs for big data analysis, providing enormous amounts of learning and insight.
Automated machine speech recognition has been an area of research for more than 60 years. The industry has built up an expansive range of business products where ASR as UI has become invaluable and inevitable forever. Consumer-centered applications are gradually requiring ASR to be effective in the full range of real-world noise and other mutilating acoustic conditions. Nonetheless, it is still a challenge to reliably recognize spoken words in practical acoustic conditions.
For example, as an additional feature in its product kit, Sharpen, a seller of a cloud-based contact center platform, provides an automated transcription service. A few years ago, in the aftermath of seeing it display its automated speech recognition platform at a meeting, Sharpen had previously become acquainted with Deepgram.
The platform is based on deep learning models and can be pre-trained in the library of calls from Deepgram. For additional training, customers can upload pre-named speech files or label speech as they go, and make the platform tailor-made. Customers can run the platform on the cloud or on-site and can use APIs to get to the speech recognition models.
ASR can be used in compliance guidelines to find explicit discussions and keywords for a range of situations, such as adherence to guidelines, quality management, reconstruction of events, and resolution of disputes. The repercussions of failure to comply are enormous, including heavy fines, ruined reputation, and legal action.
ASR can be used by team leaders in call centers to more quickly grasp the consistency of the calls from their squad. They will provide adequate preparation, cultivate information-dependent teams and analyze scripted responses to all the more likely oversight of quality control by being able to take an undeniable strategic point of view on call results. AI systems are also increasingly being used by financial organizations. ASR is used to transcribe and evaluate financial calls about anything from angry consumer grievances to illegal actions autonomously.
The automated transcription service is used by Sharpen’s customers. Since it’s free for them, many do it because, in any event, the record will be useful for them in the future. Many also rely on the platform for targeted use, including identifying robocalls by directing the platform to select certain terms or phrases usually used by robocallers and instructing sales employees.
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