Response to Speech Synthesis feedback of 2019-02-12

[Simon]

Thank you for the useful feedback (from 25 responses), regarding the Speech Synthesis course. I have clustered your comments, and my responses are below.

I have briefly summarised the most frequently mentioned positive points without adding any response, then responded to each negative point made by at least 2 people. Please do feel free to follow up and offer more feedback or clarification.

[Simon]

Positive comments

Number of people mentioning each point is given in parentheses.

Group work / interactive classes (13)

The videos (8) and subtitles / transcripts (3)

Flipped classroom format (7)

Labs (6) and specifically the tutor (2)

Milestones for the assignment (4)

speech.zone in general, including content, navigation (4)

[Simon]

Lab tasks for each week could be clearer / labs could be more structured

We will provide more class-wide instructions during the remaining lab sessions, whilst still leaving plenty of time for individual help.

[Simon]

More instructions on shell scripting / why can’t we use Python

The voice building ‘recipe’ we are using is written as shell or Scheme scripts, and it’s not easy to change that. Learning more shell scripting (in addition to what was covered in Speech Processing) is an important aspect of the course.

There some shell scripting help on the forums and I am always happy to add to that, in response to specific questions and requests.

You can use Python for everything you implement yourself, such as a text selection algorithm.

[Simon]

Could the assignment be done in pairs or groups?

I’m not a fan of pair or group work, where a single report is submitted and therefore all members of the group receive the same mark. My experience with observing this in other courses is that some students do a lot more work than others.

You can of course work together in the lab, discussing the theory and practice of speech synthesis, talking about what limited domain you might use, what kinds of hypotheses make sense, or which tool to use to implement a listening test, etc. But you must then execute the work yourself.

[Simon]

The course should have more material on neural networks and state-of-the-art methods such as Wavenet, right from the start

The course will cover all of these things, don’t worry. But it makes no sense to jump into state-of-the-art models until the foundations are solid, so that we can motivate why particular approaches are the state-of-the-art.

In other courses that I am familiar with, the state-of-the-art is covered at the start of the course, but then I find students lack the foundations and simply don’t really understand the material. They then have to backtrack and learn the foundations that are needed, sometimes on their own.

As it happens, Wavenet, in its original text-to-waveform configuration, was only very briefly the state-of-the-art and has already been superseded That’s another reason to do the state-of-the-art at the end of the course, so we can include the very latest approaches from this fast-moving field.

[Author]

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