Voice Cloning and Speech Generation with AI Training Course

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-Driven Audio Improvement and Noise Suppression is a hands-on course designed to familiarize participants with contemporary AI solutions for cleaning and enhancing audio, whether in real-time or post-production environments.

This instructor-led live training, available either online or onsite, targets beginner to intermediate professionals looking to leverage AI tools to eliminate background noise, boost voice clarity, and enhance overall audio quality for conferencing, broadcast, and surveillance applications.

Upon completing this training, participants will be able to:

• Grasp the core principles of audio signal processing and identify common noise sources.
• Utilize AI-based tools such as Krisp, Adobe Enhance, and RNNoise for practical audio enhancement.
• Incorporate noise reduction into workflows for conferencing, recording, and live broadcasting.
• 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 it.

Audio AI encompasses artificial intelligence technologies designed to interpret, analyze, generate, or interact with audio signals, including human speech, environmental sounds, and music.

This instructor-led, live training (available online or onsite) targets beginner-level professionals eager to understand how AI is applied in the audio domain for business, communication, automation, and innovation.

Upon completing this training, participants will be able to:

• Grasp the fundamentals of Audio AI and its real-world applications.
• Identify various categories of audio AI tools, such as transcription, classification, and generation.
• Examine business cases across customer service, security, compliance, and media sectors.
• Evaluate AI tools and services suitable 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 arrange.

Platforms for voice assistants, such as Amazon Alexa, Google Dialogflow, and Rasa, provide robust frameworks for creating intelligent, voice-driven applications suitable for both external and internal purposes.

This instructor-led, live training (available online or in-person) is designed for developers and design teams at an intermediate level who aim to construct, train, and launch conversational voice interfaces. These interfaces automate workflows and assist users through natural speech interaction.

Upon completing this training, participants will be capable of:

• Designing conversational flows and interaction models for voice user interfaces.
• Developing voice assistants using tools like Dialogflow and Alexa, as well as open-source frameworks such as Rasa.
• Integrating these assistants with back-end APIs, databases, and third-party services.
• Deploying assistants to smart devices or web-based voice applications.

Course Format

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

Customization Options

• For inquiries regarding customized training for this course, please reach out to us to arrange.

Audio AI refers to the technologies that facilitate the processing, recognition, and generation of voice and sound data.

This guided, live training—available both online and onsite—is designed for professionals at the beginner level who want to grasp the ethical, legal, and operational aspects of implementing audio AI within their organizations.

Upon finishing this training, participants will be equipped to:

• Pinpoint key privacy challenges associated with the capture and processing of audio data.
• Assess the compliance implications of speech-based AI systems.
• Evaluate ethical risks concerning 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.

Customization Options

• For customized training on this topic, please contact us to arrange your session.

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.