However, for speech technology to reach the potential of what it, uniquely, can do well, it still has much further to go

Finally, early identification of certain serious long-term neurological conditions is possible by monitoring subtle changes to speech. This can be done without hospital visits or even without targeting those who are at risk. Conveniently for all concerned, we all speak into our phones and computers all the time, so it would only be necessary to opt in, and give permission for your voice to be analysed, without compromising confidentiality by being recorded or listened to.

The “this” can refer to the instance of an object or class. It also changes depending on how a function is called. It is the context where you are and also changes when you are in strict vs non-strict mode. Need more reason to truly try to master it?

Nowadays, the latest developments are routinely shared, and the whole industry takes the latest ideas from Google, NVIDIA, Microsoft and a global community of university researchers, and with their blessing, extends them and applies them in new contexts, adding expertise from their own niche professions.

I have spent a lot of time working on systems which analyse accents, mispronunciations and speech impediments. Some people are difficult to understand because they have an unfamiliar accent, or are only just learning a language. We can make it easier to master pronunciation by giving them real-time feedback, but maybe we needn’t bother: morphing accents, and correcting errors in real time are both becoming a reality.

Technology to separate speech from different speakers is coming on in leaps and bounds. This is achieved both by analysing the speech more deeply, and by combining the audio data with other sources, like using multiple microphones to measure relative volume and direction, or by using input from cameras to add lip movements and facial expressions to the mix.

Speech does not only vary by accent, but also by emotional and physical state. When a condition makes someone unintelligible, it is feasible not only to improve intelligibility but to identify what is wrong, perhaps categorising emergency calls, where the speaker is affected by stroke, sedation, drunkenness, concussion, or merely identify that the caller is a child, or speaks a particular language.

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to be saying it, but somehow — almost inexplicably — the goals of the OSM community and corporate contributors seem to be largely aligned. They all want an accurate, ubiquitous map of the world that can be maintained in perpetuity as sustainably as possible.

Technology has to get as good at listening, and at speaking, as human beings are, and then — in some contexts — get better than we are. Here are a few examples from projects, which I and others have been working on lately.

In 2016, Google came up with a new approach to speech synthesis, using WaveNet, a neural network, which can be trained to generate almost any kind of sound, and then training it with real human speech. Once trained, it can be fed with quite robotic synthesized speech, and then make it sound human.

Away from our headsets, speech isn’t really as linear as I have made out. In close proximity to someone speaking, I might whisper a comment to another listener, and still go unheard by anyone else. At a dinner party, I might be involved in more than one conversation at a time, because it is easy, in the 3D space of the real-world, to keep track of who has said what, and to control the volume and direction of my speech to target a specific listener.

Finally, early identification of certain serious long-term neurological conditions is possible by monitoring subtle changes to speech. This can be done without hospital visits or even without targeting those who are at risk. Conveniently for all concerned, we all speak into our phones and computers all the time, so it would only be necessary to opt in, and give permission for your voice to be analysed, without compromising confidentiality by being recorded or listened to.

The “this” is one of the most confusing things about Javascript and with ES2020 we got “globalThis” which definitely helps to streamline things and set a clear distinction between the other “this”.

There isn’t much hand-holding when it comes to data science. It’s your responsibility to get the job done at the end of the day, and if you find yourself getting stuck, you need to be resourceful and find the answer(s) to your problem(s).

As well, you also will be required to break down your data science projects into steps. Business stakeholders care about progress and they want to see how a project is improving over time rather than waiting 5 months for the final result. Thus, you have a responsibility to communicate your progress as well as your outcome(s).

More often than not, you’ll be working with stakeholders who aren’t as tech-savvy and may not understand the projects that you are working on. Therefore, it’s your job to communicate and educate your co-workers and stakeholders in a manner that is digestible for them.