Rework transcription commit logic

At the core of the STT, there's a loop which uses Whisper to convert
audio into a transcript. As you say something, whisper sees growing
fragments of your sentence:

t0: "Hell"
t1: "Hello"
t2: "Hello, world!"

So we need some algorithm which takes these fragments and
accumulates them into an ever-growing transcript.

Previously I did this with fuzzy string matching. I'd find the region
where the two transcripts overlap and edit the two together to produce a
longer transcript. The big problem is that if there's no overlap, it's
not clear whether whisper radically changed its mind as to what was
said, or whether the user paused for a long time before saying
something new. So I'd have to reset the growing transcript.

Now I get the timestamps from Whisper and wait for it to give me the
same 3 transcripts for the last utterance. Once the transcript
stabilizes like this, I commit the text. This enables a temporally
stable, ever-growing transcript that's also quite accurate.

To prevent a latency regression, I also introduce the notion of "preview
text", which is a preview of an utterance that has not yet stabilized.
These previews do not contribute to the ever-growing transcript, but do
get fed through the rest of the app, so they show up in-game / in OBS.
Once they eventually stabilize, they get committed to the ever-growing
transcript.

This change is lightly tested!

1 files changed, 0 insertions, 165 deletions

diff --git a/Scripts/string_matcher.py b/Scripts/string_matcher.py
deleted file mode 100644
index a56308a..0000000
--- a/Scripts/string_matcher.py
+++ /dev/null
@@ -1,165 +0,0 @@
-#!/usr/bin/env python3
-
-# python3 -m pip install editdistance
-# License: MIT.
-import editdistance
-
-import typing
-
-DEBUG = False
-
-# Find the window where the distance between these two transcriptions is
-# minimized and use it to stitch them together.
-def matchStringList(old_words: typing.List[str],
-        new_words: typing.List[str], window_size = 6) -> str:
-    if old_words == new_words:
-        return " ".join(old_words)
-    elif len(old_words) >= window_size and len(new_words) >= window_size:
-        # Find the window where the cumulative string distance
-        # between the words in that window in the old/new transcription
-        # is minimized.
-        old_slice = old_words[len(old_words) - window_size:]
-
-        best_match_i = None
-        best_match_d = window_size * 1000
-
-        for i in range(0, 1 + len(new_words) - window_size):
-            new_slice = new_words[i:i + window_size]
-            cur_d = 0
-            for j in range(0, window_size):
-                cur_d += editdistance.eval(old_slice[j], new_slice[j])
-            if cur_d < best_match_d:
-                best_match_i = i
-                best_match_d = cur_d
-
-        old_prefix = old_words[0:len(old_words) - window_size]
-        overlap = new_words[best_match_i:best_match_i + window_size]
-        new_suffix = new_words[best_match_i + window_size:]
-
-        #print("Best match i:    {}".format(best_match_i))
-        #print("Window size:     {}".format(window_size))
-        #print("Old prefix:      {}".format(old_prefix))
-        #print("Overlap:         {}".format(overlap))
-        #print("New suffix:      {}".format(new_suffix))
-        return " ".join(old_prefix + new_words[best_match_i:])
-    else:
-        return " ".join(new_words)
-
-def matchSpaceDelimitedStrings(old_text: str, new_text: str, window_size = 4) -> str:
-    old_words = old_text.split()
-    new_words = new_text.split()
-    return matchStringList(old_words, new_words, window_size)
-
-def matchStrings(old_text: str, new_text: str, window_size = 3) -> str:
-    if old_text == new_text:
-        if DEBUG:
-            print("STRING MATCH exception path 1")
-        return old_text
-    elif len(new_text) == 0:
-        return old_text
-    elif len(old_text) == 0:
-        return new_text
-    elif len(old_text) >= window_size and len(new_text) >= window_size:
-        # Find the window where the cumulative string distance
-        # between the text in that window in the old/new transcription
-        # is minimized.
-
-        best_match_i = None
-        best_match_j = None
-        best_match_d = window_size * 1000
-
-        # The number of old slices to look at. Since the old text can grow
-        # unboundedly, it's crucial that we don't compare to every possible
-        # slice in the old and new transcriptions (O(N^2) time complexity).
-        # This is still wildly inefficient, but good enough for continuous
-        # transcription in a game bound by a single CPU core, like VRChat.
-        max_old_slices = 150
-        old_n_slices = min(max_old_slices, len(old_text))
-        last_old_window = len(old_text) - window_size
-        first_old_window = max(last_old_window - old_n_slices, 0)
-
-        for i in range(first_old_window, last_old_window + 1):
-            old_slice = old_text[i:i + window_size]
-
-            for j in range(0, 1 + len(new_text) - window_size):
-                new_slice = new_text[j:j + window_size]
-                cur_d = editdistance.eval(old_slice, new_slice)
-                if cur_d < best_match_d:
-                    best_match_i = i
-                    best_match_j = j
-                    best_match_d = cur_d
-
-                    if DEBUG:
-                        print("optimum at old '{}' i={} new '{}' j={} d={}".format(
-                            old_slice, i, new_slice, j, cur_d))
-
-        old_prefix = old_text[0:best_match_i]
-        overlap = new_text[best_match_j:best_match_j + window_size]
-        new_suffix = new_text[best_match_j + window_size:]
-
-        if DEBUG:
-            print("Best match i:    {}".format(best_match_i))
-            print("Best match j:    {}".format(best_match_j))
-            print("Window size:     {}".format(window_size))
-            print("Old prefix:      {}".format(old_prefix))
-            print("Overlap:         {}".format(overlap))
-            print("New suffix:      {}".format(new_suffix))
-            print("Input 1:         {}".format(old_text))
-            print("Input 2:         {}".format(new_text))
-            print("Output:          {}".format(old_prefix +
-                new_text[best_match_j:]))
-        return old_prefix + new_text[best_match_j:]
-    else:
-        if DEBUG:
-            print("STRING MATCH exception path 2")
-            print("  OLD: {}".format(old_text))
-            print("  NEW: {}".format(new_text))
-        return new_text
-
-if __name__ == "__main__":
-    # Identical transcriptions should not be changed.
-    assert(matchSpaceDelimitedStrings("This is a test case.", "This is a test case.", window_size = 3) == "This is a test case.")
-    # A suffix should be detected and ignored.
-    assert(matchSpaceDelimitedStrings("This is a test case.", "is a test case.", window_size = 3) == "This is a test case.")
-    # A lengthening suffix should be correctly appended.
-    assert(matchSpaceDelimitedStrings("This is a test", "is a test case.", window_size = 3) == "This is a test case.")
-    # A strictly longer transcription should override the old prefix.
-    assert(matchSpaceDelimitedStrings("This is a test", "This is a test case.", window_size = 3) == "This is a test case.")
-    # Paranoia: repetitive text broke the older implementation, so I included
-    # some test cases without fully understanding what the old problem was.
-    assert(matchSpaceDelimitedStrings("test test test", "test test test test test test", window_size
-        = 3) == "test test test test test test")
-    assert(matchSpaceDelimitedStrings("test test test test test test", "test test test", window_size
-        = 3) == "test test test test test test")
-
-    print(matchStrings("foo bar", "bar baz"))
-    print(matchStrings("alpha beta", "beta gamma"))
-
-    in1 = "Okay, what about now? Looks like it sort of works. Key word being sort of."
-    in2 = "okay what about now looks like it sort of works key word being sort of looks"
-    bad_out = "Okay, what about now? Looks like it sort of works. Key word being sort of works key word being sort of looks"
-    good_out = "Okay what about now looks like it sort of works key word being sort of looks"
-    good_out = "Okay, what about now? Looks like it sort of works. Key word being sort of looks"
-    print(matchStrings(in1, in2))
-    assert(matchStrings(in1, in2) == good_out)
-
-    in1 = "This repository can take"
-    in2 = "This repository contains the code for"
-    bad_out  = "This repository can tode for"
-    good_out = "This repository contains the code for"
-    assert(matchStrings(in1, in2) == good_out)
-
-    in1 = "See something."
-    in2 = "See something. Say something."
-    bad_out  = in1
-    good_out = in2
-    print(matchStrings(in1, in2))
-    assert(matchStrings(in1, in2) == bad_out)
-
-    in1 = "a" * 1000
-    in2 = "b" * 10 * 1000
-    # This should be fast (< 1 second)
-    #matchStrings(in1, in2)
-
-    print("Tests passed.")
-