Audio AI Training in Lyon

Audio AI encompasses the technologies used for processing, recognizing, and generating voice and sound data.

This instructor-led live training, available both online and onsite, is designed for beginner-level professionals seeking to grasp the ethical, legal, and operational aspects of implementing audio AI within their organizations.

Upon completion of this training, participants will be equipped to:

• Identify critical privacy challenges associated with the capture and processing of audio data.
• Evaluate the compliance requirements for speech-based AI systems.
• Assess ethical risks related to consent, surveillance, and automated decision-making.
• Facilitate the responsible procurement and implementation of audio AI tools.

Course Format

• Interactive lectures and discussions.
• Exercises focused on risk evaluation and compliance mapping.
• Guided, hands-on assessment of audio AI scenarios.

Course Customization Options

• To request customized training for this course, please contact us to arrange.

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 also allows for the evaluation of participants.

• 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-Driven Audio Enhancement and Noise Suppression is a hands-on course that introduces participants to contemporary AI tools for cleaning and improving audio quality in real-time or post-production environments.

This instructor-led training (available online or on-site) targets beginner to intermediate professionals seeking to leverage AI tools to eliminate background noise, boost voice clarity, and enhance overall audio quality for applications in conferencing, broadcasting, and surveillance.

Upon completing this training, participants will be able to:

• Grasp the fundamentals of audio signal processing and identify common sources of noise.
• Apply AI-based tools such as Krisp, Adobe Enhance, and RNNoise for practical audio enhancement.
• Integrate noise reduction techniques into conferencing, recording, or live broadcast workflows.
• Assess and select suitable tools and models based on quality, latency, and deployment requirements.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practice sessions.
• Hands-on implementation within a live-lab environment.

Course Customization Options

• To request customized training for this course, please contact us to arrange.

Platforms such as Amazon Alexa, Google Dialogflow, and Rasa provide robust frameworks for creating sophisticated, voice-enabled applications suitable for both customer-facing and internal business scenarios.

This instructor-led live training, available online or onsite, is designed for intermediate-level developers and design teams aiming to build, train, and deploy conversational voice interfaces. The course focuses on automating workflows and enhancing user support through natural speech interactions.

Upon completion of this training, participants will be equipped to:

• Design conversational flows and interaction models tailored for voice user interfaces.
• Develop voice assistants utilizing tools like Dialogflow and Alexa, alongside open-source frameworks such as Rasa.
• Integrate these assistants with backend APIs, databases, and third-party services.
• Deploy assistants onto smart devices or web-based voice applications.

Course Format

• Interactive lectures and group discussions.
• Extensive exercises and practical practice.
• Hands-on implementation within a live-lab environment.

Course Customization Options

• For those interested in a customized training session for this course, please contact us to make arrangements.

Voice cloning and speech generation with AI empowers users to replicate human voices or produce synthetic speech by leveraging deep learning models and advanced speech synthesis techniques.

This instructor-led, live training—available either online or onsite—is designed for intermediate-level professionals aiming to create, evaluate, and implement voice cloning and text-to-speech (TTS) systems in practical, real-world scenarios.

Upon completion of this training, participants will be able to:

• Grasp the fundamental concepts underlying neural speech synthesis and voice cloning.
• Assess both commercial and open-source TTS platforms.
• Clone voices from sample recordings while adhering to ethical and legal standards.
• Integrate synthetic voices into applications, interactive voice response (IVR) systems, or media pipelines.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation within a live-lab environment.

Course Customization Options

• To request a customized training session for this course, please contact us to make arrangements.

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 also allows for the evaluation of participants.

• 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 encompasses artificial intelligence technologies designed to interpret, analyze, generate, or interact with audio signals, such as human speech, environmental sounds, and music.

This instructor-led live training, available either online or on-site, is tailored for beginner-level professionals seeking to comprehend how AI is applied within the audio domain for business, communication, automation, and innovation.

Upon completing this training, participants will be capable of:

• Understanding the concept of Audio AI and its practical applications.
• Identifying various categories of audio AI tools, such as transcription, classification, and generation.
• Exploring business cases within customer service, security, compliance, and media sectors.
• Evaluating AI tools and services appropriate for enterprise audio applications.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live lab environment.

Customization Options

• For customized training requests, please contact us to make arrangements.