Ifeoluwa Oduwaiye
Mar 25, 2025
Introduction
Artificial Intelligence (AI) has been powering the customer support field since the 1980s. What we see as AI today started off as rule-based systems with one of the first being Alacrity by Alactrious Inc. Alacrity started off as a 3000-rule system that functioned using logic trees. The major setback of this approach was the rigidity of its response and its inability to handle the randomness of real-world queries.
Natural Language Processing (NLP) and Machine Learning (ML) were big game changers in this field, helping businesses transition from rigid rule-based systems to flexible query-sensitive AI-driven support systems. Now, what started as a simple chatbot has now evolved into a voice-operated assistants automating tasks like recording orders, booking appointments, collecting customer feedback, responding to queries and so on.
It’s no surprise that we now have Customer Support as a Service (CSaaS) solutions in use like Zendesk, Freshdesk, and Intercom, making huge waves and contributions to the way customer support and ultimately operations are run in companies. You might ask, how does automatic speech recognition come in?
Accessibility and Inclusion are now being more recognized by companies worldwide. Everyone wants their software to be accessible to their target audience, and a key part of that is ensuring inclusivity for people with disabilities. And hey, even if you just prefer a hands-free experience, that’s totally valid! After all, who wouldn’t want a more convenient way to interact with technology without constantly typing?
In short, customer support agents are now becoming more and more voice-operated. If you’re looking to scale your organization’s customer support processes with Automatic Speech Recognition (ASR) then you’re in the right place. Stay tuned!
Drawbacks of Traditional Customer Support
Traditional customer support wasn’t always something people looked forward to. Even with the most trained professionals, people management stills tends to be a bit dicey subject due to one major factor. It depends on people! And we all know how people can be at times, especially when they need something urgent.
That being said, the customer support industry is still large and as always been because business need sales and its always profitable to invest in your customers. Traditional customer support often relied on a set of people (first-response agents) who were on standby at landlines waiting to receive a call from customers. Then there were another set of people which attention-demanding customer conflicts were often escalated to.
You can agree with me that this wasn’t optimal. In addition to this, these businesses were often faced with high operational costs maintaining this large support teams, and their customers were often faced with long wait times, inconsistent service quality, and accessibility concerns. Language barriers also posed issues to both customer support agents and customers, making the entire customer support process unfavourable for everyone.
These systems often led to high customer churn. Transitioning from these traditional customer support systems to more automated customer support systems with speech recognition has been helping companies save money and increase customer retention. And when you add automated speech recognition into the mix, it becomes a huge game changer for businesses. How exactly does this tech transform customer support? We will be finding that out in the next section.
Photo by Icons8 Team on Unsplash
How Speech Recognition is Transforming Customer Support
The three major issues with traditional customer support systems highlighted above are high costs, long wait times, and language barriers. With ASR engines, companies can shorten language barriers between them and their customers without taking on huge expenses. How you may ask?
Here are four ways in which speech recognition is transforming customer support.
Real-time Call Transcription: ASR technology enables businesses to convert spoken conversations into text in real time, allowing customer service agents to focus on resolving issues rather than manually taking notes. This transcription improves response accuracy and ensures a complete record of the interaction, which can be referenced later for quality assurance and dispute resolution.
AI-Powered Response Generation: By integrating ASR with AI-driven chatbots, businesses can automate customer support interactions, responding to inquiries instantly without human intervention. Once speech is transcribed, AI models analyze the text and generate contextually relevant responses, reducing response times and improving service accessibility. This automation is especially beneficial for handling routine questions, such as order tracking or account updates, allowing human agents to focus on more complex issues.
Multilingual Support: ASR, combined with machine translation, allows businesses to cater to diverse customer bases by transcribing and translating speech in multiple languages. Customers can interact in their preferred language, while AI systems process the input and generate responses accordingly, eliminating language barriers in customer service. This capability is crucial for global businesses and industries like travel, e-commerce, and telecommunications, where multilingual support enhances user experience.
Sentiment Analysis & Call Insights: ASR-driven sentiment analysis enables businesses to assess customer emotions in real time, helping them proactively address dissatisfaction. With sentiment detection models, companies can analyze speech patterns, tone, and word choices in real-time to determine whether a customer is frustrated, satisfied, or neutral, allowing them to escalate urgent issues to human agents when needed. Additionally, organizations can gather insights from transcribed conversations to identify recurring concerns and optimize their service strategies.
Business Benefits of Automatic Speech Recognition
According to Qualtrics, companies could lose up to $3.7 trillion globally due to bad customer service. Additionally, Forbes 2024 Customer Service and CX research also discovered that 64% of customers would not return to a business if the customer service was not good even if they liked the product quality.
In addition to avoiding the above listed disadvantages, here are four other business benefits you stand to gain by powering your customer support processes with Automatic Speech Recognition.
Improved Efficiency: ASR streamlines customer service operations by reducing the time agents spend manually documenting calls and searching for information. With real-time transcription and AI-generated responses, inquiries are resolved faster, minimizing hold times and increasing productivity. Automated transcription also ensures accurate record-keeping, allowing businesses to track customer concerns and provide better follow-ups. As a result, companies can handle a higher volume of inquiries with the same or fewer resources.
Cost Savings: By automating customer interactions with ASR and AI chatbots, businesses can significantly cut down on labor costs associated with large support teams. Routine queries that once required human intervention can now be managed through AI-powered virtual assistants, reducing the need for 24/7 human support. Additionally, real-time transcription helps companies improve compliance and reduce legal risks by maintaining precise conversation records.
Scalability: ASR enables businesses to handle customer inquiries at scale without compromising service quality, making it an essential tool for companies experiencing growth or seasonal spikes in demand. AI-powered voice assistants and chatbots can engage with multiple customers simultaneously, ensuring no caller is left waiting. This scalability is particularly beneficial for industries such as e-commerce and finance, where high call volumes can overwhelm traditional customer service teams.
Improved Customer Experience: ASR enhances customer interactions by enabling faster responses, reducing errors, and ensuring personalized service. With powerful features like sentiment analysis, multilingual support, real-time call transcription, and contextual responses, every customer interaction feels personalized and valued. This not only enhances satisfaction but also strengthens loyalty, reducing customer churn.
Implementing AI-Powered Speech Recognition with Spitch
If you are an African entrepreneur or are an entrepreneur trying to reach the African market, Spitch has the best language technology for you. With A-grade documentation, reliable and scalable APIs that support real-time transcription and speech generation, along with its support for multilingual translation and tone marking, you should look no further.
And quite frankly, its easy to use too. Implementing ASR for your customer support agents using Spitch has never been easier using Spitch’s speech transcription, speech generation, and machine translation features. It’s as easy as plug-and-play. Here’s how you can implement ASR using Spitch.
Speech Transcription (ASR)
Spitch’s Speech Transcription, also known as Speech-To-Text (STT) or ASR, converts spoken language into written text across its supported languages (English, Yoruba, Hausa and Igbo). This feature can be used to enable accurate record-keeping and immediate processing of customer calls. This feature is vital for scaling customer support as it facilitates real-time call transcription through its streaming service, allowing support agents to quickly review and respond to customer queries.
To implement this feature, follow the guide in the docs here.
Speech Generation
The Speech Generation, or Text-To-Speech (TTS) feature transforms text into natural-sounding speech in languages such as English, Yoruba, Hausa, or Igbo, allowing companies to deliver personalized, voice-based responses to customers, and create more engaging and human-like interaction in automated support systems.
Spitch offers four distinct voice options for each language to help companies with different brand personlities and customer expectations. To get started implementing this feature in your customer support systems, head over to our docs here.
Machine Translation
The Machine Translation feature in Spitch enables seamless conversion from one language to another, ensuring that support content can be accurately and efficiently translated in real time. This capability is especially critical for businesses operating in multilingual regions, where customers may communicate in different languages. By integrating machine translation with ASR, organizations can increase accessibility and cater for a wider audience.
To implement this feature, check out our docs here.
Real-World Use Cases of AI-Powered Customer Support
Call Center Automation
Call centers handle thousands of customer inquiries daily, many of which are repetitive, such as billing inquiries, account updates, or service requests. ASR allows businesses to automate these interactions by transcribing calls in real time and using AI-powered virtual agents to handle routine conversations. When a call is initiated, ASR converts the spoken words into text, which is then processed by a Natural Language Understanding (NLU) model to determine the user’s intent. Based on this understanding, the virtual agent can either resolve the inquiry, direct the call to the right department, or escalate complex issues to human agents. This automation streamlines operations, reducing call wait times and allowing human agents to focus on higher-value tasks.
The banking sector has widely adopted ASR-driven call center automation. For example, Bank of America implemented its AI-powered assistant, Erica, which has handled over 1.5 billion customer interactions since its launch. By automating simple banking tasks such as balance inquiries, transaction history retrieval, and card activations, the bank has significantly reduced customer wait times while improving operational efficiency. According to a report by Juniper Research, AI chatbots and voice assistants in banking are expected to handle 90% of customer interactions by 2025, reducing costs and increasing customer satisfaction.
AI-Powered Chatbots and Voice Assistants
AI-powered chatbots and voice assistants leverage ASR to process spoken customer queries and generate natural language responses. When a user speaks, ASR transcribes the speech into text, which is then analyzed by an AI chatbot to determine intent and retrieve the most relevant response. This approach enables businesses to offer instant support, resolve frequent inquiries, and provide self-service options without requiring human intervention. Chatbots can be deployed across multiple channels, including websites, mobile apps, and smart speakers, ensuring 24/7 availability and scalability for customer interactions.
In the e-commerce industry, Amazon’s Alexa is a leading example of ASR-powered voice assistants. Alexa not only helps users with online shopping but also provides customer support by answering common questions and tracking order statuses. According to a Statista report, over 130 million Alexa-enabled devices have been sold worldwide This shift towards AI-driven support has improved response times and reduced operational costs for companies using ASR-based virtual assistants.
Sentiment Analysis and Customer Insights
ASR not only transcribes customer interactions but also enables businesses to analyze speech for sentiment and emotional tone. Sentiment analysis uses AI models to evaluate whether a customer’s speech conveys frustration, satisfaction, or urgency. Businesses can leverage these insights to assess customer experience, detect emerging issues, and adjust their support strategies accordingly. By identifying patterns in customer sentiment, companies can improve their product offerings, refine communication strategies, and proactively address pain points.
One notable example is Delta Air Lines, which uses ASR and sentiment analysis to monitor customer interactions and gauge satisfaction levels. By analyzing transcribed conversations, Delta can detect frustration in customers’ voices and escalate calls to human agents for resolution. The airline has reported a 12% increase in customer satisfaction after implementing sentiment analysis tools, demonstrating the effectiveness of ASR in enhancing service quality. A study by Salesforce found that 80% of customers are more likely to stay loyal to brands that understand and address their concerns proactively. This highights the importance of ASR-driven sentiment analysis in customer retention.
Multilingual Customer Support
Global businesses serve customers from diverse linguistic backgrounds, making multilingual support a necessity. ASR integrated with machine translation enables real-time speech-to-text conversion in multiple languages, ensuring that language barriers do not hinder customer service interactions. When a customer speaks in their native language, ASR transcribes the conversation, and an AI-powered translation engine converts the text into the support team’s preferred language. This allows businesses to provide seamless customer support across different regions without needing a multilingual workforce.
One major industry that benefits from multilingual ASR is hospitality, where companies like Marriott International use AI-powered translation tools to assist international guests. By integrating ASR-driven multilingual chatbots into their customer service systems, Marriott provides real-time translations for guests in over 50 languages, enhancing the guest experience. According to a report by CSA Research, 75% of consumers prefer to buy products and services in their native language, emphasizing the business value of multilingual AI-driven customer support.
Conclusion
AI-powered speech recognition is rapidly transforming customer support, making interactions more efficient, scalable, and personalized. As technology continues to evolve, we can expect even more advanced ASR capabilities, including improved natural language understanding, sentiment analysis, and fully AI-driven customer interactions.
Companies like Spitch are the forefront of the field, developing technology and resources to support companies with customer support. With efficient features for ASR, speech generation, and multilingual translation, companies can easily scale and digitize their customer support systems with our APIs.
This article introduced you to methods and techniques for scaling your company’s customer support using Spitch. If you’re looking to transform your customer service with cutting-edge AI and real-time speech recognition, don’t wait. Sign up now and start revolutionizing your support operations!
