The Voice AI that revolutionizes conversation analysis : Voice Analytics


How is Voice AI revolutionizing conversation analysis?

Oral communication is the oldest and fastest method of exchanging information.

Integrating Voice AI into your customer service seems essential: your customers will be taken care of more quickly, and your teams will be freed from repetitive, time-consuming tasks. What's more, voice recognition can now analyze users' conversations, intentions and even emotions. This enables you to enrich your database and identify new business opportunities!

Want to know more about this AI technology? Are you looking for the perfect tool to improve your Customer Relations and gain in efficiency? Choose ZAION Voice AI and improve not only your Customer Experience, but also your Employee Experience!


What is Voice AI?

Artificial Intelligence (AI) is a computer science discipline that implements techniques to enable machines to imitate human intelligence. Voice AI, as a sub-category, understands and imitates natural language through speech. It responds to user requests using voice recognition and machine learning technologies.

Voice AI has become an integral part of our daily lives, in both the private and professional spheres. The reason for its success? It enables us to obtain reliable answers very quickly, while remaining free to move about as we please. The software understands us instantly and detects our speech errors. Today, this artificial intelligence technology can be found in numerous applications: voice assistants such as Siri or Google Assistant at home and on the telephone, callbots that relieve call centers... Voice AI adapts to all communication channels.


How voice recognition works (ASR)

Automatic Speech Recognition (ASR) is software capable of communicating in natural language. It understands intonation, syntax and pronunciation, as well as the different accents and dialects in the human voice. To do this, the tool processes the spoken request, captured from a microphone. The voice is transformed into an electrical wave signal and then into a digital signal. The software converts it into phonemes and then reconstructs the whole into words. Machine learning technology takes care of the speech and voice analysis, improving with each conversation.


Natural language processing encompasses the understanding - Natural Language Understanding (NLU) - and generation - Natural Language Generation (NLG) - of natural language, drawing on a variety of techniques from multiple disciplines, such as artificial intelligence, computer science, data science, machine learning, text analysis and linguistic sciences, including semantics. By integrating these fields, we can provide in-depth training for computers, enabling them to grasp and interpret human language, whether written or spoken.

Natural Language Understanding (NLU)

Natural Language Understanding (NLU) is a sub-discipline of NLT (NLP) that focuses on the ability of machines to extract and interpret information from human language. This discipline involves the conversion of text or speech into structured data that machines can process and analyze. Key NLU tasks include:

  • Syntactic analysis: determine the grammatical structure of a sentence and identify the relationships between words.
  • Semantic analysis: understanding the meaning of words and phrases in context


Natural Language Generation (NLG)

Natural Language Generation (NLG) is the other side of TLN, and involves creating natural language text or speech from structured data. This discipline is essential for creating coherent, relevant answers to user queries, as well as for generating summaries, translations or automated responses. NLG's main tasks include:

  • Discourse planning: determining the logical organization of the text to be generated.
  • Information aggregation: combining different sources of information to generate a coherent discourse.
  • Phrase generation: convert structured data into natural phrases.
  • Text revision: check and correct grammatical and semantic errors in the generated text.


Voice Analytics, ZAION's voice AI solution

Voice data is an untapped goldmine for many companies.

While 80% of them record this data, two-thirds don't make full use of it for commercial purposes, according to a 2021 study by Opus Research. Thanks to artificial intelligence and machine learning, this is about to change.

At ZAION, we have developed Voice Analytics, a solution for analyzing voice conversations.


Voice Analytics: voice AI for conversation analysis

Voice Analytics, our solution based on ZAION technology, harnesses artificial intelligence to transform voice data into actionable information. By analyzing calls in depth (transcription, tone, emotion, turns of speech, silences, intentions, etc.), Voice AI identifies users' positive and negative feelings, and continually refines itself. As a result, companies can enrich their customer knowledge with detailed, real-time reports.


Voice Analytics: a revolution in customer relations

Voice Analytics goes beyond conversation analysis, transforming data into a decision-making tool. The solution is based on three main pillars:

  • Agent scoring and coaching: evaluate customer service performance and set up personalized coaching sessions;
  • Compliance measurement: alerts in the event of escalation or non-compliance with sales or regulations;
  • Customer insights: detect trends and identify business opportunities based on conversations (product improvements, business rules, etc.).


Voice AI for all sectors and company sizes

Our Zaion Voice Analytics solution is accessible to companies of all sizes and industries, enabling the integration of Voice AI to improve customer service and Employee Experience. By adopting this technology, you'll gain a competitive edge and improved productivity over the long term.

Voice AI, embodied by our Zaion Voice Analytics solution, is paving the way for a revolution in Customer Relations. By fully exploiting voice data, you can improve your customer service, compliance and understanding of your customers' needs. It's time to embrace Voice AI to stay competitive and thrive in an increasingly demanding market.

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