Speech recognition courses can help you learn the fundamentals of audio processing, language modeling, and transcription techniques. You can build skills in feature extraction, acoustic modeling, and implementing neural networks for voice recognition. Many courses introduce tools like Python libraries, TensorFlow, and Kaldi, that support developing speech recognition systems and applying AI to enhance user interactions in applications such as virtual assistants and automated transcription services.

Skills you'll gain: Computer Vision, Applied Machine Learning, Digital Signal Processing
Intermediate · Course · 1 - 4 Weeks

Skills you'll gain: Supervised Learning, Computer Vision, Recurrent Neural Networks (RNNs), Machine Learning Methods, Convolutional Neural Networks, Matplotlib, Data Visualization, Probability & Statistics, Deep Learning, Classification Algorithms, Artificial Intelligence, Plotly, Statistical Analysis, Data Visualization Software, Statistical Hypothesis Testing, Machine Learning, Seaborn, Applied Machine Learning, Digital Signal Processing, Statistical Inference
Intermediate · Specialization · 3 - 6 Months

SkillsBooster Academy
Skills you'll gain: Generative AI, AI Product Strategy, Brand Strategy, Content Creation, Business Communication, Storytelling, Media Production, Brand Awareness, Social Media Content, Digital Design, Business Ethics, Marketing Communications, Creative Thinking, Influencing, Business Transformation, Entrepreneurship, Creative Problem-Solving, Media and Communications, Customer Engagement, Digital Marketing
Beginner · Course · 1 - 3 Months

Skills you'll gain: Serverless Computing, Computer Vision, Image Analysis, Amazon Web Services, AI Enablement, Amazon S3, AWS Identity and Access Management (IAM), Text Mining, Data Processing, Unstructured Data
Intermediate · Course · 1 - 4 Weeks

DeepLearning.AI
Skills you'll gain: Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Computer Vision, Transfer Learning, Deep Learning, Image Analysis, Hugging Face, Natural Language Processing, Artificial Neural Networks, Tensorflow, Embeddings, Supervised Learning, Keras (Neural Network Library), Applied Machine Learning, Machine Learning, MLOps (Machine Learning Operations), Debugging, Performance Tuning, PyTorch (Machine Learning Library), Data Preprocessing
Build toward a degree
Intermediate · Specialization · 3 - 6 Months

Skills you'll gain: PyTorch (Machine Learning Library), Large Language Modeling, Embeddings, Generative AI, Natural Language Processing, Transfer Learning, Recurrent Neural Networks (RNNs), Data Ethics, Artificial Neural Networks, Classification Algorithms, Model Evaluation, Data Preprocessing, Feature Engineering
Intermediate · Course · 1 - 4 Weeks

Skills you'll gain: Natural Language Processing, Large Language Modeling, Model Evaluation, Recurrent Neural Networks (RNNs), Classification Algorithms, Data Ethics, Responsible AI, Text Mining, Transfer Learning, Machine Learning Methods, PyTorch (Machine Learning Library), Artificial Neural Networks, Data Preprocessing, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Data Processing, Embeddings, Machine Learning, Data Analysis, Data Cleansing
Intermediate · Specialization · 3 - 6 Months

Skills you'll gain: Natural Language Processing, Microsoft Azure, Artificial Intelligence, Artificial Intelligence and Machine Learning (AI/ML), Analytics, Automation, Application Development
Beginner · Course · 1 - 4 Weeks

Skills you'll gain: Case Studies, User Experience Design, Business Analysis, Natural Language Processing, Application Programming Interface (API), Application Deployment, Application Development, Artificial Intelligence, Systems Integration, Scalability
Beginner · Course · 1 - 4 Weeks

Alberta Machine Intelligence Institute
Skills you'll gain: Generative AI, Generative Model Architectures, Generative Adversarial Networks (GANs), Vision Transformer (ViT), Image Analysis, Embeddings, Autoencoders, Convolutional Neural Networks, Responsible AI, Computer Vision, Music, Recurrent Neural Networks (RNNs)
Mixed · Course · 1 - 4 Weeks

Northeastern University
Skills you'll gain: Natural Language Processing, Model Evaluation, Embeddings, Text Mining, Artificial Intelligence, Recurrent Neural Networks (RNNs), Artificial Neural Networks, Deep Learning, Machine Learning, Unsupervised Learning, Dimensionality Reduction
Mixed · Course · 1 - 3 Months

Northeastern University
Skills you'll gain: Unsupervised Learning, Supervised Learning, Regression Analysis, Applied Machine Learning, Statistical Modeling, Machine Learning Algorithms, PyTorch (Machine Learning Library), Statistical Methods, Statistical Machine Learning, Machine Learning, Predictive Analytics, Predictive Modeling, Machine Learning Software, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Classification Algorithms, Logistic Regression, Unstructured Data, Model Evaluation, Dimensionality Reduction
Intermediate · Course · 1 - 3 Months
Speech recognition is a technology that enables machines to understand and process human speech. It converts spoken language into text, allowing for a range of applications from virtual assistants to transcription services. The importance of speech recognition lies in its ability to enhance accessibility, streamline communication, and improve user experience across various platforms. As more industries adopt this technology, understanding speech recognition becomes crucial for professionals looking to stay relevant in a rapidly evolving digital landscape.‎
Careers in speech recognition span various fields, including technology, healthcare, and education. Potential job roles include speech recognition engineer, data scientist specializing in natural language processing, and software developer for voice-activated applications. Additionally, positions in user experience design and accessibility consulting are also available, as companies seek to create more inclusive products. With the growing demand for voice technology, opportunities in this area are expanding.‎
To pursue a career in speech recognition, you should develop a blend of technical and analytical skills. Key areas include programming languages such as Python, understanding machine learning algorithms, and familiarity with natural language processing (NLP). Additionally, knowledge of audio signal processing and data analysis can be beneficial. Soft skills, such as problem-solving and effective communication, are also important as they enable collaboration in multidisciplinary teams.‎
Some of the best online courses for learning about speech recognition include the Mastering AI: Neural Nets, Vision System, Speech Recognition Specialization and the AI Applications: Computer Vision and Speech Recognition. These courses provide foundational knowledge and practical skills necessary for working with speech recognition technologies.‎
Yes. You can start learning speech recognition on Coursera for free in two ways:
If you want to keep learning, earn a certificate in speech recognition, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎
To learn speech recognition, start by exploring online courses that cover the fundamentals of the technology. Engage with interactive content, participate in discussions, and work on practical projects to reinforce your understanding. Additionally, consider joining online communities or forums where you can connect with others interested in speech recognition. This collaborative approach can enhance your learning experience and provide valuable insights.‎
Typical topics covered in speech recognition courses include the basics of audio processing, machine learning techniques, natural language processing, and the development of speech recognition systems. You may also explore advanced topics such as deep learning applications in speech recognition and the ethical considerations surrounding voice technology. These subjects provide a comprehensive understanding of how speech recognition works and its applications.‎
For training and upskilling employees in speech recognition, consider courses like the AI Workflow: Machine Learning, Visual Recognition and NLP. Such programs are designed to equip professionals with the necessary skills to implement speech recognition technologies effectively in their organizations. These courses can help enhance productivity and innovation within the workforce.‎