From voice cloning and noise suppression to emotion detection and speech synthesis, Audio AI is reshaping how machines hear — and how people are heard.
These instructor-led courses dive into the technologies powering intelligent sound: audio signal processing, deep learning architectures, and real-time voice interaction systems.
Participants can join online live training via interactive remote desktop, or opt for onsite sessions in Dartmouth, where each hands-on lab tackles real-world challenges like echo removal, voice detection, or audio synthesis.
From in-house R&D labs to product innovation teams, organizations in Dartmouth can host onsite training at their own location or collaborate face-to-face at a NobleProg training center built for sonic experimentation.
Also known as Voice AI, Intelligent Audio, or Speech AI, this training is ideal for developers, product teams, and researchers pushing the boundaries of machine listening.
NobleProg – Your Local Training Provider
Dartmouth - Metropolitan Place
99 Wyse Road, Dartmouth, Canada, B3A 4S5
Metropolitan Place is an ocean-front building, close to Alderney Landing and home to leading businesses. Motorway exits and the local ferry terminal are located close by, and restaurants cafes are easily accessible for lunch.
Audio Classification and Event Detection with ML is a technical course focused on building machine learning models to classify audio and detect sound events in real-world environments.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level data professionals who wish to apply machine learning techniques to analyze and classify audio data for use in public safety, manufacturing, smart cities, and multimedia analytics.
By the end of this training, participants will be able to:
Understand how sound events are modeled and categorized using ML.
Preprocess audio data using feature extraction techniques like MFCC and spectrograms.
Build, train, and evaluate models for audio classification and event detection.
Deploy ML models for real-time or batch-based audio processing in enterprise or embedded settings.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
AI-Powered Audio Enhancement and Noise Reduction is a practical course designed to introduce participants to modern AI tools used to clean and improve audio in real time or post-production settings.
This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to apply AI tools to remove background noise, enhance voice clarity, and improve audio quality across conferencing, broadcast, and surveillance use cases.
By the end of this training, participants will be able to:
Understand the fundamentals of audio signal processing and common sources of noise.
Use AI-based tools like Krisp, Adobe Enhance, and RNNoise for real-world audio enhancement.
Integrate noise reduction into conferencing, recording, or live broadcast workflows.
Evaluate and choose appropriate tools and models based on quality, latency, and deployment needs.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
Voice assistant platforms like Amazon Alexa, Google Dialogflow, and Rasa offer powerful frameworks for developing intelligent, voice-driven applications for both public and internal use cases.
This instructor-led, live training (online or onsite) is aimed at intermediate-level developers and design teams who wish to build, train, and deploy conversational voice interfaces that automate workflows and support users naturally via speech.
By the end of this training, participants will be able to:
Design conversational flows and interaction models for voice UIs.
Develop voice assistants using tools like Dialogflow, Alexa, and open-source frameworks such as Rasa.
Integrate assistants with back-end APIs, databases, and third-party services.
Deploy assistants to smart devices or web-based voice apps.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
Voice cloning and speech generation with AI allows users to replicate human voices or generate synthetic speech using deep learning models and speech synthesis techniques.
This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to create, evaluate, and apply voice cloning and TTS systems in real-world projects.
By the end of this training, participants will be able to:
Understand the core concepts behind neural speech synthesis and voice cloning.
Evaluate commercial and open-source TTS platforms.
Clone voices from sample recordings using ethical and legal guidelines.
Integrate synthetic voices into applications, IVRs, or media pipelines.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
Speech recognition and transcription using AI involves converting spoken language into written text through machine learning models and natural language processing systems.
This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to implement, evaluate, and optimize AI-powered speech-to-text solutions for real-world use cases.
By the end of this training, participants will be able to:
Understand how modern speech recognition models are trained and deployed.
Evaluate open-source and commercial APIs for speech-to-text transcription.
Handle multilingual and domain-specific transcription challenges.
Build simple transcription workflows for different audio sources.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
Audio AI refers to artificial intelligence technologies that interpret, analyze, generate, or interact with audio signals, including human speech, environmental sounds, and music.
This instructor-led, live training (online or onsite) is aimed at beginner-level professionals who wish to understand how AI is applied in the audio domain for business, communication, automation, and innovation purposes.
By the end of this training, participants will be able to:
Understand what Audio AI is and how it is used in real-world settings.
Identify different categories of audio AI tools (e.g., transcription, classification, generation).
Explore business cases in customer service, security, compliance, and media.
Evaluate AI tools and services suitable for enterprise audio applications.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
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