Contact center agents
Claudia Ancuta

Claudia Ancuta

October 26, 2023

The Right Speech-to-Text Solution For a Contact Center


Contact centers are vital to customer experience, but poor interactions can lead to losses.

The global contact center market reached a staggering $340 billion as of 2022, but subpar customer experiences can cost companies $62 billion in the US alone. This is largely due to inadequate contact center interactions.

To improve efficiency, contact centers need to start with the foundation: voice calls.

Enhancing voice processing capabilities can unlock unprecedented efficiency gains. Automated speech recognition (ASR) solutions are a godsend in this regard. They can help contact centers understand customer interactions, identify patterns, and extract meaningful information such as customer intent, sentiment, and preferences.

As speech-to-text capabilities continue to evolve, ASR has the potential to transform contact center operations.

This article explores how to select the optimal ASR provider/solution for call center solution providers.

At a Glance: What is Automated Speech Recognition (ASR)

Put simply, speech-to-text technology enables computers to convert spoken language or audio input into written text. 

Speech Recognition systems use advanced algorithms and machine learning techniques to process and interpret spoken words, accurately transcribing them into textual form.

Without getting into the technical nitty-gritty, here is how speech-to-text systems work. 

  1. The speech signal (the audio) is processed to enhance the audio quality and remove noise or distortions. 
  2. Acoustic modeling techniques are applied to analyze speech features and identify phonetic units, such as individual sounds or syllables. 
  3. Language modeling is used to predict the most likely sequence of words based on the context and grammar of the language being spoken. 
  4. Decoding algorithms are employed to match the acoustic and language models, generating the most probable transcription of the spoken input.

The accuracy and performance of ASR systems have significantly improved over the years, thanks to advancements in deep learning, neural networks, and large-scale training data. However, challenges remain, such as dealing with background noise, handling various accents and languages, and ensuring the privacy and security of the transcribed data.

The Need For Automatic Speech Recognition Technology in Contact Center Operations

As customer interactions in contact centers predominantly occur through voice calls, harnessing the power of speech recognition becomes paramount in meeting the following expectations.

Improving Process Efficiency

Traditional call monitoring and evaluation methods are time-consuming, largely manual, and resource-intensive. Automatic speech recognition streamlines this process, enabling real-time transcription, automated call analysis, and extracting valuable conversation insights. This saves valuable time for agents and supervisors and enhances operational efficiency.

Enhancing Customer Experience

An accurate transcript can be used by Analytics to detect customer sentiment and intent, enabling agents to respond empathetically (or accordingly). Also, ASR-based contact center solutions help improve customer experience directly or indirectly. (More on that later.)

Gathering Actionable Process Insights

By analyzing speech to text data, contact centers can identify recurring issues, trends, and areas for improvement. These enable them to improve agent training programs, optimize processes, and identify product and service enhancement opportunities.

Compliance and Quality Assurance

Voice technology helps contact centers in regulated industries, such as finance or healthcare, comply with stringent guidelines by recording and analyzing calls and conversations.

Agent Enablement

With automatically transcribed calls (with intent analysis) at their disposal in real time, agents can focus more on actively listening to the caller and be better equipped to address their concerns. These ultimately translate to conversations that help provide personalized assistance. 

The Challenges of Implementing Speech Recognition Technology in Contact Centers

While automatic speech recognition technology holds significant potential to enhance contact center operations and empower contact center solution providers, leveraging it can be an easier-said-than-done affair. As with any technology implementation/adoption, several challenges exist when going up and running with speech to text.

Accuracy and Error Rates

Speech recognition systems may encounter difficulties accurately transcribing speech, especially in noisy environments or with speakers with distinct accents or dialects. Needless to say, high error rates can impact the quality of transcriptions and hinder the effectiveness of real-time monitoring, sentiment analysis, and data analysis, among other use cases. Also, errors in correctly identifying speakers can impact the accuracy of transcriptions and subsequent analyses.

Language and Vocabulary Support

Contact centers often handle interactions in multiple languages and industry-specific terminologies. General-purpose speech-to-text solutions may struggle to accurately recognize and transcribe them. 

Integration and Compatibility

Integrating ASR technology with existing contact center infrastructure, telephone systems, and software applications can entail implementation hurdles, compatibility issues, and configuration complexities. 

The Relevance of Custom Models For ASR

While generic speech-to-text models often struggle with domain-specific terminology, accents, and speech patterns unique to contact center operations, custom models are tailored to the contact center's domain. They incorporate industry-specific jargon, regional accents, and speech characteristics unique/relevant to the contact center solution provider’s clients. 

By training speech recognition models on domain-specific data, such as recorded customer interactions and call center conversations, contact center solution providers can achieve higher accuracy and performance in speech recognition. 

By analyzing and incorporating feedback from transcriptions, contact center solution providers can refine their models, reroute around specific ASR challenges and optimize performance.

That said, building ASR tech from scratch is often not the ideal way to go. 

Why Building ASR Tech From Scratch is a Bad Idea For Contact Centers and Contact Center Solution Providers

Most contact center solution providers (or contact center CIOs, for that matter) eyeing the possibilities of leveraging speech to text tech will generally be swayed towards developing ASR solutions from scratch, tailored specifically to meet their client's requirements. As enticing as it may seem, this approach is far from the ideal path. 

Here’s why:

Building automatic speech recognition solutions from the ground up requires substantial investments in terms of time, resources, and expertise. It involves assembling a team of skilled professionals, acquiring vast amounts of data for training purposes, and developing complex algorithms and models.

While you may have the data, developing custom speech to text  models requires expertise in machine learning, data annotation, and domain knowledge. Also, continuous model maintenance and training are crucial to ensure the accuracy and effectiveness of  your in-house ASR tech. This entails keeping up with the latest research, technology, and industry standards. 

These can detract you from core business priorities.

Just as you don't need to build a tea shop to enjoy a cup of tea, there is no need to reinvent the wheel when it comes to speech to text solutions.

Benefits of Partnering With an ASR Technology Expert/Solution Provider

“Leave it to the experts.”

This line best sums up why as a contact center solution provider, you should entrust ASR to the expertise of a dedicated Speech-to-Text solution provider. 

Here is the elaborate version of the answer:

  • ASR experts have dedicated their time and resources to refining and perfecting the intricacies of speech recognition technology
  • They possess the necessary expertise to tackle challenges related to acoustic variability, language support, speaker diarization, and data privacy, among others
  • They possess the domain-specific knowledge and tools required to adapt speech-to text technology (or build custom ASR models)  to meet your specific needs
  • You can focus on what you do best while enhancing your offerings and providing your contact center with accurate and efficient speech recognition capabilities.
  • You wouldn’t need to divert valuable resources and attention from your core business objectives

How Call Center Solution Providers Can Choose The Right Speech-to-Text Solution

Since speech recognition technology will be a fundamental component of your offering as a contact center solution provider, thorough vetting of the ASR solution provider is paramount.

Here are some criteria for the same:

Solution’s Prowess

Examine the speed of the ASR provider's transcription services. Determine whether the provider can handle multi-channel audio or if they are limited to single-channel processing. Inquire whether they can search audio directly for specific words or phrases.

Solution Alignment

Ensure the speech-to-text solution aligns with your contact center solution's specific requirements and objectives. Assess the provider's expertise in serving the contact center industry, their understanding capability, and your challenges.

Track Record and Reputation

Research their history, client testimonials, and case studies to gain insights into their experience, success stories, and customer satisfaction. 

Accuracy and Performance

Request demos or trials to evaluate the solution firsthand. Assess the ASR technology's accuracy and performance metrics, such as word error rate (WER) and its ability to handle diverse accents, languages, and speech patterns. 

Customization and Flexibility

Speech-to-text solution providers should offer flexibility in adapting their solutions to your domain-specific needs and speech characteristics. Evaluate the scope of their delivering custom automatic speech recomodels. 

Integration and Compatibility

Assess the provider's capabilities for seamless integration with your existing contact center infrastructure. Consider their support for telephony systems, IVR platforms, call routing software, and other relevant tools. 

Support and Maintenance

Evaluate the provider's support and maintenance services. Consider the availability of customer support, documentation, and training resources. 

Data Security and Privacy

Assess their adherence to industry-standard data protection regulations, data encryption practices, access controls, and secure storage measures. 

Roadmap and Innovation

Ensure the speech-to-text solution provider continuously invests in research and development to stay at the forefront of the industry. A forward-thinking Automatic Speech Recognition provider will bring ongoing improvements, new features, and advanced capabilities to your contact center solution.

This careful evaluation will enable you to deliver an exceptional and value-added offering to your clients, setting you apart from competitors and driving success in the contact center industry.

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