Nils Lenke’s stories
Dragon uses deep learning for more accurate speech recognition.

Everybody is special in how we use language – how we speak, the words we use, etc. In an earlier blog post, we saw how speech recognition systems eliminate this variation by training on speech and language data that cover many accents, age groups, or other variations in speaking style you might think of. This […]

Seeing is like hearing for machines and human brains

As noted in previous posts, there is an array of neural net machine learning approaches that are simply more than just “deep.” In a time when Neural Networks are increasingly popular for advancing voice technologies, language understanding and AI, it’s interesting that many of the current approaches were originally developed for image or video processing. […]

How you can use machine learning and natural language methods to accurately answer customer service questions

If you’ve been reading my series, you know that AI and machine learning (ML) can have a powerful impact on delivering the best possible customer care experience.  Specifically, we’re applying “big knowledge” for customer service tasks. What does this mean? The first task we want to look at is “passage retrieval,” or finding relevant text […]

Machine learning turns bags of words from big data into big knowledge for customer care

In my last post, I discussed how human agents and human assisted virtual agents (HAVAs) can work together when machine learning and artificial intelligence are applied to customer care systems. Now let’s take it a step further. In machine learning you often need to compare or “match” things.  For example, when you are looking for […]

DFKI students use nuance speech tools to create interactive IoT applications

In my last blog post, I explained how we use different types of Neural Networks for both ASR and NLU. We already touched upon DNNS, RNN, and NeuroCRF, and I did not even mention that we use CNNs (Convolutional Neural Networks) for the “intent” discovery aspect of NLU. Does this sound confusing? Fortunately for end-users […]

An agent in a call center supports virtual agents

This post is part of a series that explores the use of human assisted virtual agents, and how machine learning and artificial intelligence are being applied to ultimately improve the customer experience.   Customer support automation is an important playing field for today’s Artificial Intelligence and Machine Learning systems. This no longer means primarily call […]

How many Neural Nets does it take to catch the big fish in Machine Learning?

Deep Neural Nets (DNN) having taken over Machine Learning these last few years, driving headlines and discussion within the industry and the media.  That said, we’re just scratching the surface with Neural Nets, which are evolving and changing with many different approaches and challenges to solve. “Standard” DNNs are unidirectional: information flows in just one […]

Students from the University of Koblenz-Landau built Lisa, a helpful social robot who can communicate with humans and perform daily tasks.

With 75.4 million Baby Boomers in the U.S. alone, it’s undeniable that a large percentage of the population is growing older. This means unique challenges for this generation: fluctuating health needs, concerns about economic independence, and, eventually, even the ability to independently perform common daily tasks. As a result, people are now beginning to think […]

Variation can improve accuracy of speaker verification for voice biometrics

Recently, I shared some thoughts on variation in ASR and TTS, and naturally as a speech scientist, I have more to say on the topic of variation. In language identification we eliminate all variation parameters except the language in which a message is spoken; the only goal is to classify bits of speech into one […]

Speech systems need to observe and deal with pauses and other variation to elicit more natural communication between man and machine

Communication is full of variation and variety.  When you’re exposed to unfamiliar languages it is very hard to recognize patterns – often hard even in native languages as people from different regions, demographics, dialects, and being in different environments (say a noisy or a quiet place) and situations speak differently. In the 19th and 20th […]

How machine speech systems use and make sense of ellipses rhetorical devices

This post is part of a series that explores the unique complexities of human speech and, consequently, how we create systems that appropriately take these complexities into account when interacting with users. Rhetorical devices are commonly used in our speech, and while we naturally come to use, recognize, and understand them in our daily lives, […]

in communication, speech systems are built to interpret and use rhetorical devices like anaphora

This post is part of a series that explores the unique complexities of human speech and, consequently, how we create systems that appropriately take these complexities into account when interacting with users. Rhetorical devices are commonly used in our speech, and while we naturally come to use, recognize, and understand them in our daily lives, […]

in communication, speech systems are built to make sense of and use rhetorical devices like paraphrase

This post is part of a series that explores the unique complexities of human speech and, consequently, how we create systems that appropriately take these complexities into account when interacting with users. Now that I’ve introduced you to the prominence of rhetorical devices in everyday speech in my first post, let’s move on to another […]

The ancient Greeks discovered rhetorical devices which are now common in everyday language - something we need to specially design speech systems to accommodate

Intricacies in our speech are inherent in our everyday lives; they are acquired over time and ultimately become natural ways for us to interact with the people – and things – in the world around us. Speaking to devices the same way we speak to each other and having them understand us, though, is not […]

deep-machine-learning-metaphors

As movies like “Ex Machina,” “Her,” “The Imitation Game,” and others continue to hit the big screen, we are also seeing a lot of excitement around “deep learning.”  Just for fun, I entered “applies deep learning to” into a well-known search engine and according to the hundreds of results, “deep learning” is being applied to: […]

Childlike curiosity, being comfortable with a blank page... Nuance researchers share what qualities they think a good researcher possesses

As you may have read a few days ago, a scientific paper (on the mass of the Higgs boson) set a new record for having more than 5,000 authors. This made me think about the two sides of Science: on the one hand, science is the evolution of concepts, theories, and ideas, as they come […]

Nuance Research Conference 2015 explored R&D topics like Deep Neural Nets, Artificial Intelligence, Natural Language Understanding, Anaphora, and more

Nuance recently concluded its Nuance Research Conference (“NRC”) in Montreal, where the Company’s diverse research team from all over the world comes together for four days to dig deep into the next generation of voice and touch innovation. If this year’s conference had a theme, it was “Inspired by Humans.” The event began with a […]

nuance-research-conference-2014

Isn’t innovation, the root of which is the Latin word “nova,” meaning “new,” always about new things? Well, it turns out there are (at least) two types of innovation: one that you can see and one that you cannot see, or not easily see, anyway. The former involves creating entirely new products – or at […]