lmmx · April 2, 2025 02:27 · Sep 27, 2022 · Sep 27, 2022 · Sep 27, 2022 · Sep 27, 2022
diff --git a/diarise.py b/diarise.py
@@ -44,4 +44,5 @@ def td_time_format(td):
     for order in speaker_order
     for speaker, (start_idx, stop_idx) in order.items()
 ]
-rollup_df = df.from_records(rollup_records)
+rollup_df = df.from_records(rollup_records)
+# rollup_df["stype"] = rollup_df.stype.replace("SPEAKER_00", "Name0").replace("SPEAKER_01", "Name1").replace("SPEAKER_02", "Name2").replace("SPEAKER_03", "Name3")
diff --git a/diarise.py b/diarise.py
@@ -23,8 +23,7 @@ def td_time_format(td):
 # via https://stackoverflow.com/a/71214440/2668831
 speaker_runs = {
     speaker: [
-        # np.unique(np.array([int(g) for g in grp])[[0,-1]]).tolist()
-        np.array([int(g) for g in grp])[[0,-1]].tolist()
+        np.array(grp)[[0,-1]].tolist()
         for grp in np.split(group, np.where(np.diff(group) != 1)[0]+1)]
     for speaker, group in df.groupby("stype").agg("tbeg_fmt").groups.items()
 }

diff --git a/diarise.py b/diarise.py
@@ -7,23 +7,42 @@
 
 # RTTM format https://catalog.ldc.upenn.edu/docs/LDC2004T12/RTTM-format-v13.pdf
 with open("foo.rttm", "w") as rttm:
-  diarization.write_rttm(rttm)
+    diarization.write_rttm(rttm)
 
 import pandas as pd
 df = pd.read_csv("foo.rttm", sep=" ", header=None, usecols=[3,4,7], names="tbeg tdur stype".split())
 
 def td_time_format(td):
-  parts = td.components
-  return f"{parts.minutes}:{parts.seconds:02}.{parts.milliseconds:03}"
+    parts = td.components
+    return f"{parts.minutes}:{parts.seconds:02}.{parts.milliseconds:03}"
 
 df["tbeg_fmt"] = pd.to_timedelta(df.tbeg, unit="s").apply(td_time_format)
 df["tend_fmt"] = pd.to_timedelta(df.tbeg + df.tdur, unit="s").apply(td_time_format)
 
 # Get consecutive speaker runs, or single points
 # via https://stackoverflow.com/a/71214440/2668831
 speaker_runs = {
-  speaker: [
-    np.unique(np.array([int(g) for g in grp])[[0,-1]]).tolist()
-    for grp in np.split(group, np.where(np.diff(group) != 1)[0]+1)]
-  for speaker, group in x.groups.items()
-}
+    speaker: [
+        # np.unique(np.array([int(g) for g in grp])[[0,-1]]).tolist()
+        np.array([int(g) for g in grp])[[0,-1]].tolist()
+        for grp in np.split(group, np.where(np.diff(group) != 1)[0]+1)]
+    for speaker, group in df.groupby("stype").agg("tbeg_fmt").groups.items()
+}
+
+# 'Roll up' the timestamps over consecutive runs by inverting the dict
+speaker_order = sorted(
+    [{speaker: run} for speaker, runs in speaker_runs.items() for run in runs],
+    key=lambda d: [*d.values()]
+)
+rollup_records = [
+    {
+        "tbeg": df.tbeg[start_idx],
+        "tdur": df.tbeg[stop_idx] + df.tdur[stop_idx] - df.tbeg[start_idx],
+        "stype": df.stype[start_idx],
+        "tbeg_fmt": df.tbeg_fmt[start_idx],
+        "tend_fmt": df.tend_fmt[stop_idx],
+    }
+    for order in speaker_order
+    for speaker, (start_idx, stop_idx) in order.items()
+]
+rollup_df = df.from_records(rollup_records)
diff --git a/diarise.py b/diarise.py
@@ -0,0 +1,29 @@
+# ffmpeg -i foo.m4a foo.wav
+
+from pyannote.audio import Pipeline
+
+pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization")
+diarization = pipeline("foo.wav")
+
+# RTTM format https://catalog.ldc.upenn.edu/docs/LDC2004T12/RTTM-format-v13.pdf
+with open("foo.rttm", "w") as rttm:
+  diarization.write_rttm(rttm)
+
+import pandas as pd
+df = pd.read_csv("foo.rttm", sep=" ", header=None, usecols=[3,4,7], names="tbeg tdur stype".split())
+
+def td_time_format(td):
+  parts = td.components
+  return f"{parts.minutes}:{parts.seconds:02}.{parts.milliseconds:03}"
+
+df["tbeg_fmt"] = pd.to_timedelta(df.tbeg, unit="s").apply(td_time_format)
+df["tend_fmt"] = pd.to_timedelta(df.tbeg + df.tdur, unit="s").apply(td_time_format)
+
+# Get consecutive speaker runs, or single points
+# via https://stackoverflow.com/a/71214440/2668831
+speaker_runs = {
+  speaker: [
+    np.unique(np.array([int(g) for g in grp])[[0,-1]]).tolist()
+    for grp in np.split(group, np.where(np.diff(group) != 1)[0]+1)]
+  for speaker, group in x.groups.items()
+}
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