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Why speech recognition capabilities are vital for contact center software

Why speech recognition capabilities are vital for contact center software
Corentin Messerschmidt
Corentin Messerschmidt Head of Innovation Lab at Odigo

Voice is still the dominant channel in customer service, which means optimizing speech recognition software using the latest best-in-class technology is a must. The good news is that solution providers are making quality improvements to speech processing software that are producing new sources of data that are not just usable, but actionable. Corentin Messerschmitt explains.

February 18, 2022 3 min of reading

Speech recognition, or speech processing, is the analysis of sound in such a way as to make words and phrases searchable. When it comes to customer experience (CX), speech processing software is essential to gathering customers’ information and improving communication and experience with them. Efforts are being made by the top solutions providers in Contact Center as a Service (CCaaS) to continuously benefit from the best improvements in speech recognition capabilities.

Why? Simply put, the rumors of the voice channel’s demise have been greatly exaggerated. Though millennials make more use of non-voice channels, as CX Today reports, they by no means make up the majority of customers. Thanks to the prevalence of other demographics, as well as the desire for connection in a world embattled by COVID-19, voice is still the dominant channel. 

Speech recognition and language learning

Developers are making quality improvements to speech processing software that are producing new sources of data that are not just usable, but actionable. Innovations like speech-to-text, which converts spoken language into a readable format (and its cousin, text-to-speech, which translates the written word into audible content) are being increasingly optimized, and by 2025 40% of all inbound voice communications to contact centers will use speech-to-text technology. 

However, the process of optimizing speech recognition is a lot like teaching somebody a foreign language. If you’re reading this article, chances are that English may not be your native tongue, and you might even be taking language lessons for business purposes in your off-hours. That’s why you may find such a comparison helpful when discussing the must-haves for speech processing software.

Speech processing software must be able to handle real-time conversations

A prime reason for learning a foreign language as an adult is to be able to converse functionally in business settings. Of course, conversation goes beyond mere understanding and regurgitating of words. The more about speech cues you learn — especially subtle ones — the better your conversation skills, and therefore the more valuable your interactions with colleagues, will be. Learning conversation skills require more than simple input, however. It requires practice and repetition.

There is a strong parallel to be drawn here with speech recognition. Voice bots must be able to handle conversations in order to help customers. Machine learning (ML) software can be trained to recognize cues from past interactions with customers so that automated systems can handle routine interactions, such as questions about a store’s hours, without the need for a human agent to intervene. The better a bot can pick up on conversational nuance, the better served your customer base will be. 

Speech recognition software should be able to pick up on context

It goes without saying that the language used in business settings will not be the same as that used in social contexts, which is a tricky thing for adult language learners. If a programmer expects to be able to use the same language with their 5-on-5 football teammates as they do at work, it grates and problematizes the process of smooth conversation. 

Similarly, the language needed for optimized automated customer service options should be able to deeply learn the vernacular and themes of its intended context. It’s very common for specific business domains, whether they’re brands, products or even entire verticals, to have specialized language and contexts. Luckily, speech recognition software is up to the task of learning the language that your business operations are predicated upon. Improvements in speech processing based on leaps in artificial intelligence (AI) and natural language processing (NLP) technologies make speech recognition more trustworthy than ever. Their potential to answer the growing need for personalization in CX makes its inclusion in CCaaS solutions a must.

Speech processing software positively reinforces brand identity

If you manage to do well in language school, it means that your teacher did a decent job of imparting knowledge onto you. Quality teachers enlarge the reputations of language schools, which are brands in and of themselves that compete fiercely with each other. And it must also not be forgotten that students are customers who consider the teachers a school has when deciding which school to enroll in. As such, teachers are a component of a school’s brand identity.

Another strong component of brand identity is security. When you enroll in classes, schools create records of your transactions and learning progress, all of which is confidential. Contact centers also work with a lot of customer data such as passwords and transaction history. Speech recognition-powered security measures such as voice biometrics can help cut down on the mundanities of CX, like the necessity of answering security questions, while making sure that the only ones who can get access are the customers themselves. A brand that takes security and privacy seriously is a successful brand.

Secure your brand’s reputation with speech processing software

Language is an undeniable part of business, whether it’s for learning purposes or speech processing software that helps you deliver top-notch CX. If your contact center is in need of speech recognition capabilities that can learn reliably and respond to specific customer needs, Odigo embeds best-in-class technology based on AI and NLP into our CCaaS solutions.

Corentin Messerschmidt
Head of Innovation Lab at Odigo

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