Voice AI Glossary
Voice AI: A technology category covering everything related to everything below.
Automatic Speech Recognition (ASR): Technology that converts spoken words into text.
Transcription: Same as above
Speech-to-text: Same as above
Text-to-Speech (TTS): The process of converting text into spoken voice output.
Speech Synthesis: Technology that converts a linguistic representation into speech.
Voice Recognition: Technology that recognizes and differentiates individual voices.
Voice Assistant: AI-powered software that can perform tasks or services based on voice commands.
Dialog Systems: Systems that can converse with humans using text or voice.
Chatbot: A software application used to conduct an online chat conversation via text or text-to-speech.
Wake Word Detection: The ability of a device to activate upon hearing a specific phrase.
Sentiment Analysis: The process of determining the emotional tone behind a series of words.
Voice Biometrics: Using a person's voice for identification and authentication.
Acoustic Modeling: The process of using audio signals to identify linguistic elements.
Voice User Interface (VUI): An interface that allows users to interact with systems through voice commands.
Interactive Voice Response (IVR): A technology that allows a computer to interact with humans through the use of voice and DTMF tones input via a keypad.
ASR Custom Vocabulary: A tailored set of words or phrases specifically added to an Automatic Speech Recognition system to enhance its ability to recognize and accurately transcribe industry-specific jargon, technical terms, or unique names.
Conversational Intelligence: The application of AI technologies to understand, process, and respond to human language in a natural and contextually relevant manner, typically used in chatbots and virtual assistants.
Conversational Voice AI: AI systems designed to engage in natural, human-like voice conversations, understanding spoken language and responding verbally in a coherent and context-aware manner.
Voice Latency: The time delay experienced between the moment a voice input is given and when the voice AI system responds or processes the input.
AI Accent Localization: The use of artificial intelligence to modify or adapt the accent of synthesized speech to match a specific regional or cultural speech pattern.
Speech-to-Speech Translation: The process of converting spoken language in one language into spoken language in another, using AI to both recognize and generate speech in real-time.
AI Noise Cancellation: The application of AI algorithms to identify and eliminate unwanted background noise from audio input, enhancing voice clarity.
AI Noise Suppression: The use of AI to reduce the volume and impact of background noise in a voice signal without completely eliminating it.
AI Noise Removal: The process where AI technologies detect and remove background noises from audio streams, improving the quality and intelligibility of the voice signal.
Active Noise Cancellation: A technology found in Headsets that actively counteracts ambient noise by generating a sound wave that is phase-inverted to the unwanted noise, effectively canceling it out.
AI Voice Agents (Bots): AI programs designed to simulate human conversation, often used in customer service and personal assistant applications, responding to voice commands and queries.
AI Meeting/Call Assistant: An AI tool that assists in virtual meetings or calls by providing services such as noise cancellation, accent conversion, translation, real-time transcription, meeting summaries, action item tracking, or participant engagement analysis.
AI Voice Conversion: The use of AI to change the characteristics of a voice input into a different voice, often altering factors like pitch, tone, and accent.
AI Live Assist: An AI-powered tool that provides real-time assistance or support during live interactions, such as customer service calls or online chats, often through automated suggestions, information retrieval, or direct intervention.
Speech Analytics: The process of analyzing recorded or live voice data using AI to extract meaningful information, such as sentiment analysis, topic detection, or speech pattern analysis, often used in customer service and business intelligence.
Natural Language Processing (NLP): The ability of a computer program to understand, interpret, and generate human language.
Natural Language Understanding (NLU): A subset of NLP focused on understanding the intent and context of spoken or written language.
Digital Signal Processing (DSP): The analysis, manipulation, and improvement of digital signals, typically audio or visual data, using algorithms to filter, compress, or extract meaningful information.
Speaker Diarization: The process of partitioning an audio stream into homogeneous segments according to the identity of the speaker, effectively determining "who spoke when”.