Guidelines for giving a talk
- The primary purpose of your talk should be to show what is interesting
about what you have done. People who find the ideas interesting can
then read your paper for details. Do not think of the talk as a
substitute for reading the paper (although it should be a substitute
for a quick skimming of the paper).
If you concentrate on the low-level details, you may well find yourself
talking to only 5-10% of the audience.
- The secondary purpose of your talk should be make your paper more
accessible to those who found it interesting. Help the audience
visualize what you describe in the paper, and try to bolster their
intuitions about what you are doing and why.
To these ends, your presentation should not be your paper cutdown to
fit into the allowed time. Instead, you should take advantage of the
different media available in the talk to present information that
is difficult to explain in the paper. For example, a complex structure
or chart can be more easily understood when the presenter uses pointing
to identify the various elements and their interrelationships during
Transparency overlays can dramatically illustrate a variety of differences
or changes (they can also get out-of-hand).
Judicious use of color can also enhance comprehension of complex
structures or charts.
- In planning your presentation, a major tactical concern should be to
keep the memory load imposed on the audience within reasonable bounds.
Remember that although you immediately recognize the various abbreviations,
vocabulary, symbols and formulas used in your talk, most of the audience
will be much slower to identify their meanings and import. If the
audience has to spend too much time making such associations, they will
get behind in following your presentation. Also, the audience may lose
track of your higher level ideas attempting to leave room to remember
- Provide a balance between what, why, how, and how well.
At a previous meeting, many people came away from a group of talks
complaining that they knew what the success percentage was, but that
they had little idea of what the author was actually trying to do,
and no idea of what methods and techniques had been used to accomplish
the results. This situation also raised questions about whether the
author had gotten good results, or simply good numbers.
NB: this is not an invitation to short-change the how well portion
of the presentation.
- The use of abbreviations on transparencies is often necessitated by
the limited amount of space available. To make it easier for the
audience to follow the presentation, you can point at the abbreviation
while speaking its full name (or a variant). For example, if you
use the abbreviation "ATIS", you could say "Air Travel Planning"
(a variant which is more descriptive and more common than the official
name - "Air Travel Information System").
Remember that although the audience may be expected to know/understand
the underlying term or name, a substantial portion of them do not use it
as an abbreviation, and thus will not quickly recognize it.
- Do not expect the audience to remember much detail from a previous
slide. For example, if comparing two approaches, do not summarize
each approach on different slides and expect the audience to be able
to see the differences. Presenting such comparisons is often the
trickiest part of planning a presentation because there is so little
room on a transparency (assuming that you are using a font large enough
to read) -- you often want to show multiple comparisons/trends, but
can't fit all the relevant items on a single slide, but wish to avoid
the discontinuity of switching slides.
- Present numbers in context. ****
- When you present how well your approach worked, try to go beyond
percent correct. Try to provide insight into what the numbers
mean. Try to characterize what you got right and what you got
wrong. This characterization is then useful in predicting whether
or not your approach can be improved/extended to cover data you
currently get wrong. If your approach is unlikely to be extendable
to cover many of the cases you currently get wrong, can it identify
those cases so that you could conceive of it handing them off to
another system built to handle such "hard" cases.
Examples better than definitions
- Skipping lesser detail: Unless there was something controversal,
innovative or otherwise noteworthy in your evaluation methodology,
much of that detail can be left in your paper. For example, few
in the audience will care whether you reserved 10% or 20% of the
corpus for test data.
No Theorems, unless revealing