- How to apply machine learning and deep learning methods to audio analysis - Nov 19, 2019.
Find out how data scientists and AI practitioners can use a machine learning experimentation platform like Comet.ml to apply machine learning and deep learning to methods in the domain of audio analysis.
- A 2019 Guide for Automatic Speech Recognition - Sep 24, 2019.
In this article, we’ll look at a couple of papers aimed at solving the problem of automated speech recognition with machine and deep learning.
- Build Your First Voice Assistant - Sep 6, 2019.
Hone your practical speech recognition application skills with this overview of building a voice assistant using Python.
- Practical Speech Recognition with Python: The Basics - Jul 9, 2019.
Do you fear implementing speech recognition in your Python apps? Read this tutorial for a simple approach to getting practical with speech recognition using open source Python libraries.
- Comparison of the Top Speech Processing APIs - Dec 28, 2018.
There are two main tasks in speech processing. First one is to transform speech to text. The second is to convert the text into human speech. We will describe the general aspects of each API and then compare their main features in the table.
- Interspeech 2018: Highlights for Data Scientists - Dec 24, 2018.
Key highlights from the Interspeech conference, with topics covering end-to-end models for automatic speech recognition, information theory approach to deep learning, speech processing and education, and more.
- ODSC India Highlights: Deep Learning Revolution in Speech, AI Engineer vs Data Scientist, and Reinforcement Learning for Enterprise - Sep 26, 2018.
Key takeaways and highlights from ODSC India 2018 conference about the latest trends, breakthroughs and revolutions in the field of Data Science and Artificial Intelligence
- Building an Audio Classifier using Deep Neural Networks - Dec 15, 2017.
Using a deep convolutional neural network architecture to classify audio and how to effectively use transfer learning and data-augmentation to improve model accuracy using small datasets.
- Bill Inmon on Hearing The Voice Of Your Customer - Dec 7, 2017.
This post explores the importance of hearing your customer, and how to use sentiment analytics and other technologies to achieve this goal and avoid going out of business.
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- Top KDnuggets tweets, Nov 15-21: DeepLearning is “shallow”: here are underlying concepts you need - Nov 27, 2017.
Also: New Poll: Data Science / Machine Learning methods you used; The amazing predictive power of conditional probability in Bayes Nets; The 10 Statistical Techniques Data Scientists Need to Master.
- Machine Learning Reveals 9 Elements of Deal-Closing Sales - Sep 26, 2017.
The data science team at Gong.io analyzed over 67,000 sales calls/demos to understand the patterns that close deals. Here is what we found.
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- Deep Learning Zero to One: 5 Awe-Inspiring Demos with Code for Beginners, part 2 - Jul 1, 2017.
Here are deep learning examples and demos you can just download and run, including Spotify Artist Search using Speech APIs, Symbolic AI Speech Recognition, and Algorithmia API Photo Colorizer.
- Deep Learning Zero to One: 5 Awe-Inspiring Demos with Code for Beginners - Jun 26, 2017.
Here are deep learning demos and examples you can just download and run. No Math. No Theory. No Books.
- Top KDnuggets tweets, Mar 15-21: Reverse-engineering a $500M AI company in one week; Climate Change Denial and CO2 Emissions - Mar 22, 2017.
Also Hastie, Tibshirani and Friedman - The Elements of Statistical Learning Book PDF; Getting Close and Personal w. #MachineLearning #Algorithms; Open Source Toolkits for Speech Recognition.
- Open Source Toolkits for Speech Recognition - Mar 14, 2017.
This article reviews the main options for free speech recognition toolkits that use traditional Hidden Markov Models and n-gram language models.
- Artificial Intelligence and Speech Recognition for Chatbots: A Primer - Jan 26, 2017.
Bot bots bots... Read this overview of how artificial intelligence and natural language processing are contributing to chatbot development, and where it all goes from here.
- Data Science of Sales Calls: 3 Actionable Findings - Jan 19, 2017.
How does AI help sales and marketing teams in the organisation? Let’s understand Dos and don’ts of sales calls with the help of analysis of over 70,000+ B2B SaaS sales calls.
- Achieving Human Parity in Conversational Speech Recognition - Dec 13, 2016.
This is an overview of the paper which outlines, for the first time, a system has been developed that exceeds human performance in one of the most difficult of all human speech recognition tasks: natural conversations held over the telephone.
- Data Science of Sales Calls: The Surprising Words That Signal Trouble or Success - Sep 29, 2016.
While not as profound a problem as uncovering the secrets of the universe, how to conduct a successful sales conversation is an age-old problem, impacting millions of people every day.
- Microsoft is Becoming M(ai)crosoft - Apr 25, 2016.
This post is an overview and discussion of Microsoft's increasing investment in, and approach to, artificial intelligence, and how their philosophy differs from their competitors.
- Nurture by Numbers – Big Data and Children - Mar 5, 2016.
Driven by rising healthcare costs and competitions for top schools, more organisations and individuals are turning to Big Data and Analytics to try and give their children the upper hand.
- Around the World in 60 Days: Getting Deep Speech to Work in Mandarin - Feb 24, 2016.
Baidu continues to make impressive gains with deep learning. Their latest achievement centers on Mandarin speech recognition, which you can read about here from the researchers involved in the project.
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- Xerox Research Centre India: Research Scientist/Engineer: Speech and Signal Processing - Oct 5, 2015.
Speech group main goal is to enable Human-Computer-Smartphone interactions to be speech enabled in our day-to-day and professional lives.
- Talking Machine – Deep Learning in Speech Recognition - May 2, 2015.
A summary about an episode on the talking machine about deep neural networks in speech recognition given by George Dahl, who is one of Geoffrey Hinton’s students and just defended his Ph.D last month.