Update app.py

app.py

@@ -22,6 +22,7 @@ from pyannote.audio import Pipeline
 from pyannote.core import Annotation, Segment, Timeline
 import datetime as dt
 
+enableDenoise = False
 earlyCleanup = True
 
 # [None,Low,Medium,High,Debug]
@@ -37,7 +38,22 @@ def printV(message,verbosityLevel):
     global verbosity
     if verbosity>=verbosityLevel:
         print(message)
+        
+def get_display_name(speaker, fileIndex):
+    """Return the user-assigned display name for a speaker, or the original label."""
+    renames = st.session_state.speakerRenames
+    if fileIndex < len(renames) and speaker in renames[fileIndex]:
+        return renames[fileIndex][speaker]
+    return speaker
 
+def apply_speaker_renames_to_df(df, fileIndex, column="task"):
+    """Replace speaker_## labels in a DataFrame column with display names."""
+    if column not in df.columns:
+        return df
+    df = df.copy()
+    df[column] = df[column].apply(lambda s: get_display_name(s, fileIndex))
+    return df
+    
 @st.cache_data
 def convert_df(df):
    return df.to_csv(index=False).encode('utf-8')
@@ -66,13 +82,27 @@ def save_data(
     scheduler.append(data)
 
 def processFile(filePath):
+    global attenLimDb
     global gainWindow
     global minimumGain
     global maximumGain
     print("Loading file")
     waveformList, sampleRate = su.splitIntoTimeSegments(filePath,600)
     print("File loaded")
-    waveformEnhanced = su.combineWaveforms(waveformList)    
+    enhancedWaveformList = []
+    if (enableDenoise):
+        print("Denoising")
+    for w in waveformList:
+        if (enableDenoise):
+            newW = enhance(dfModel,dfState,w,atten_lim_db=attenLimDB).detach().cpu()
+            enhancedWaveformList.append(newW)
+        else:
+            enhancedWaveformList.append(w)
+    if (enableDenoise):
+        print("Audio denoised")
+    waveformEnhanced = su.combineWaveforms(enhancedWaveformList)    
+    if (earlyCleanup):
+        del enhancedWaveformList
     print("Equalizing Audio")
     waveform_gain_adjusted = su.equalizeVolume()(waveformEnhanced,sampleRate,gainWindow,minimumGain,maximumGain)
     if (earlyCleanup):
@@ -128,7 +158,7 @@ def updateCategoryOptions(resultIndex):
     #st.info(f"After update: {st.session_state.categorySelect}")
 
 def updateMultiSelect():
-    currFileIndex = file_names.index(st.session_state["select_currFile"])
+    currFileIndex = st.session_state.file_names.index(st.session_state["select_currFile"])
     st.session_state.resetResult = True
     for i, category in enumerate(st.session_state['categories']):
         st.session_state[f'multiselect_{category}'] = st.session_state['categorySelect'][currFileIndex][i]
@@ -168,92 +198,113 @@ def analyze(inFileName):
             st.session_state.summaries[currFileIndex]["df3"] = df3
             printV(f'Set df3',4)
             
-            df4_dict = {}
+            # --- Build df4 ---
             nameList = st.session_state.categories
             extraNames = []
             valueList = [0 for i in range(len(nameList))]
             extraValues = []
-            
+
             for sp in speakerNames:
                 foundSp = False
                 for i, categoryName in enumerate(nameList):
                     if sp in categorySelections[i]:
-                        #st.info(categoryName)
                         valueList[i] += su.sumTimes(currAnnotation.subset([sp]))
                         foundSp = True
                         break
-                if foundSp:
-                    continue
-                else:
+                if not foundSp:
                     extraNames.append(sp)
                     extraValues.append(su.sumTimes(currAnnotation.subset([sp])))
-            extraPairsSorted = sorted(zip(extraNames, extraValues), key=lambda pair: pair[0])
-            extraNames, extraValues = zip(*extraPairsSorted)
+
+            if extraNames:
+                extraPairsSorted = sorted(zip(extraNames, extraValues), key=lambda pair: pair[0])
+                extraNames, extraValues = list(zip(*extraPairsSorted))
+                extraNames = list(extraNames)
+                extraValues = list(extraValues)
+            else:
+                extraNames, extraValues = [], []
+
             df4_dict = {
-                    "values": valueList+list(extraValues),
-                    "names": nameList+list(extraNames),
-                }
+                "values": valueList + extraValues,
+                "names": nameList + extraNames,
+            }
             df4 = pd.DataFrame(data=df4_dict)
             df4.name = "df4"
             st.session_state.summaries[currFileIndex]["df4"] = df4
+            printV(f'Set df4', 4)
 
-            printV(f'Set df4',4)
-            
-            speakerList,timeList = su.sumTimesPerSpeaker(oneVoice)
+            # --- Build df5 ---
+            speakerList, timeList = su.sumTimesPerSpeaker(oneVoice)
             multiSpeakerList, multiTimeList = su.sumMultiTimesPerSpeaker(multiVoice)
-            summativeMultiSpeaker = sum(multiTimeList)
-            basePercentiles = [sumNoVoice/currTotalTime,
-                                 sumOneVoice/currTotalTime,
-                                 sumMultiVoice/currTotalTime
-                                ]
-            df5 = pd.DataFrame(
-                {
-                    "ids" : ["NV","OV","MV"]+[f"OV_{i}" for i in range(len(speakerList))]
-                                +[f"MV_{i}" for i in range(len(multiSpeakerList))],
-                    "labels" : ["No Voice","One Voice","Multi Voice"] + speakerList + multiSpeakerList,
-                    "parents" : ["","",""]+["OV" for i in range(len(speakerList))]
-                                +["MV" for i in range(len(multiSpeakerList))],
-                    "parentNames" : ["Total","Total","Total"]+["One Voice" for i in range(len(speakerList))]
-                                +["Multi Voice" for i in range(len(multiSpeakerList))],
-                    "values" : [sumNoVoice,
-                                sumOneVoice,
-                                sumMultiVoice,
-                                ] + timeList + multiTimeList,
-                    "valueStrings" : [su.timeToString(sumNoVoice),
-                                su.timeToString(sumOneVoice),
-                                su.timeToString(sumMultiVoice),
-                                ] + su.timeToString(timeList) + su.timeToString(multiTimeList),
-                    "percentiles" : [basePercentiles[0]*100,
-                                     basePercentiles[1]*100,
-                                     basePercentiles[2]*100] +
-                                    [(t*100) / sumOneVoice * basePercentiles[1] for t in timeList] +
-                                    [(t*100) / summativeMultiSpeaker * basePercentiles[2] for t in multiTimeList],
-                    "parentPercentiles" : [basePercentiles[0]*100,
-                                     basePercentiles[1]*100,
-                                     basePercentiles[2]*100] +
-                                    [(t*100) / sumOneVoice for t in timeList] +
-                                    [(t*100) / summativeMultiSpeaker for t in multiTimeList],
-                    
-                }
-            )
+
+            speakerList = list(speakerList) if speakerList else []
+            timeList = list(timeList) if timeList else []
+            multiSpeakerList = list(multiSpeakerList) if multiSpeakerList else []
+            multiTimeList = list(multiTimeList) if multiTimeList else []
+
+            summativeMultiSpeaker = sum(multiTimeList) if multiTimeList else 1
+            safeOneVoice = sumOneVoice if sumOneVoice > 0 else 1
+
+            basePercentiles = [
+                sumNoVoice / currTotalTime,
+                sumOneVoice / currTotalTime,
+                sumMultiVoice / currTotalTime,
+            ]
+
+            timeStrings = su.timeToString(timeList) if timeList else []
+            multiTimeStrings = su.timeToString(multiTimeList) if multiTimeList else []
+            if isinstance(timeStrings, str):
+                timeStrings = [timeStrings]
+            if isinstance(multiTimeStrings, str):
+                multiTimeStrings = [multiTimeStrings]
+
+            n_ov = len(speakerList)
+            n_mv = len(multiSpeakerList)
+
+            df5 = pd.DataFrame({
+                "ids": ["NV", "OV", "MV"] + [f"OV_{i}" for i in range(n_ov)] + [f"MV_{i}" for i in range(n_mv)],
+                "labels": ["No Voice", "One Voice", "Multi Voice"] + speakerList + multiSpeakerList,
+                "parents": ["", "", ""] + ["OV"] * n_ov + ["MV"] * n_mv,
+                "parentNames": ["Total", "Total", "Total"] + ["One Voice"] * n_ov + ["Multi Voice"] * n_mv,
+                "values": [sumNoVoice, sumOneVoice, sumMultiVoice] + timeList + multiTimeList,
+                "valueStrings": [
+                    su.timeToString(sumNoVoice),
+                    su.timeToString(sumOneVoice),
+                    su.timeToString(sumMultiVoice),
+                ] + timeStrings + multiTimeStrings,
+                "percentiles": [
+                    basePercentiles[0] * 100,
+                    basePercentiles[1] * 100,
+                    basePercentiles[2] * 100,
+                ] + [(t * 100) / safeOneVoice * basePercentiles[1] for t in timeList]
+                  + [(t * 100) / summativeMultiSpeaker * basePercentiles[2] for t in multiTimeList],
+                "parentPercentiles": [
+                    basePercentiles[0] * 100,
+                    basePercentiles[1] * 100,
+                    basePercentiles[2] * 100,
+                ] + [(t * 100) / safeOneVoice for t in timeList]
+                  + [(t * 100) / summativeMultiSpeaker for t in multiTimeList],
+            })
             df5.name = "df5"
             st.session_state.summaries[currFileIndex]["df5"] = df5
-            printV(f'Set df5',4)
-            
-            speakers_dataFrame,speakers_times = su.annotationToDataFrame(currAnnotation)
+            printV(f'Set df5', 4)
+
+            # --- Build speakers_dataFrame, df2 ---
+            speakers_dataFrame, speakers_times = su.annotationToDataFrame(currAnnotation)
             st.session_state.summaries[currFileIndex]["speakers_dataFrame"] = speakers_dataFrame
             st.session_state.summaries[currFileIndex]["speakers_times"] = speakers_times
 
             df2_dict = {
-                "values":[100*t/currTotalTime for t in df4_dict["values"]],
-                "names":df4_dict["names"]
+                "values": [100 * t / currTotalTime for t in df4_dict["values"]],
+                "names": df4_dict["names"],
             }
             df2 = pd.DataFrame(df2_dict)
             st.session_state.summaries[currFileIndex]["df2"] = df2
-            printV(f'Set df2',4)
-    except ValueError as e:
-        print(f"Value Error: {e}")
-        pass
+            printV(f'Set df2', 4)
+    except Exception as e:
+        import traceback
+        print(f"Error in analyze: {e}")
+        traceback.print_exc()
+        st.error(f"Debug - analyze() failed: {e}")
 
 #----------------------------------------------------------------------------------------------------------------------
 
@@ -271,6 +322,7 @@ secondDifference = 5
 gainWindow = 4
 minimumGain = -45
 maximumGain = -5
+attenLimDB = 3
 
 isGPU = False
 
@@ -287,6 +339,10 @@ except RuntimeError as e:
     print(f"Using {device} instead.")
 #device = xm.xla_device()
 
+if (enableDenoise):
+    # Instantiate and prepare model for training.
+    dfModel, dfState, _ = init_df(model_base_dir="DeepFilterNet3")
+    dfModel.to(device)#torch.device("cuda"))
 pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization-3.1")
 pipeline.to(device)#torch.device("cuda"))
 
@@ -294,6 +350,8 @@ pipeline.to(device)#torch.device("cuda"))
 # Long-range usage
 if 'results' not in st.session_state:
     st.session_state.results = []
+if 'speakerRenames' not in st.session_state:
+    st.session_state.speakerRenames = []
 if 'summaries' not in st.session_state:
     st.session_state.summaries = []
 if 'categories' not in st.session_state:
@@ -367,6 +425,8 @@ if uploaded_file_paths is not None:
         st.session_state.categorySelect.append(tempCategories)
     while (len(st.session_state.summaries) < len(valid_files)):
         st.session_state.summaries.append([])
+    while (len(st.session_state.speakerRenames) < len(valid_files)):
+        st.session_state.speakerRenames.append({})
         
     st.session_state.file_names = file_names
 
@@ -473,6 +533,8 @@ if st.sidebar.button("Load Demo Example"):
         st.session_state.categorySelect.append(tempCategories)
     while (len(st.session_state.summaries) < len(valid_files)):
         st.session_state.summaries.append([])
+    while (len(st.session_state.speakerRenames) < len(valid_files)):
+        st.session_state.speakerRenames.append({})
         
     with st.spinner(text=f'Loading Demo Sample'):
         # RTTM load as filler
@@ -484,6 +546,8 @@ if st.sidebar.button("Load Demo Example"):
                 totalSeconds = segment.end
         st.session_state.results = [(annotations, totalSeconds)]
         st.session_state.summaries = [{}]
+        while len(st.session_state.speakerRenames) < 1:
+            st.session_state.speakerRenames.append({})
         speakerNames = annotations.labels()
         st.session_state.unusedSpeakers = [speakerNames]
         with st.spinner(text=f'Analyzing Demo Data'):
@@ -533,6 +597,23 @@ try:
        
         newCategory = st.sidebar.text_input('Add category', key='categoryInput',on_change=addCategory) 
 
+        st.sidebar.divider()
+        st.sidebar.subheader("Rename Speakers")
+        st.sidebar.caption("Replace SPEAKER_## labels with real names.")
+        current_renames = st.session_state.speakerRenames[currFileIndex]
+        for sp in speakerNames:
+            current_label = current_renames.get(sp, "")
+            new_name = st.sidebar.text_input(
+                f"{sp}",
+                value=current_label,
+                placeholder=f"e.g. John",
+                key=f"rename_{currFileIndex}_{sp}"
+            )
+            if new_name.strip():
+                st.session_state.speakerRenames[currFileIndex][sp] = new_name.strip()
+            elif sp in st.session_state.speakerRenames[currFileIndex]:
+                del st.session_state.speakerRenames[currFileIndex][sp]
+
         catTypeColors = su.colorsCSS(3)
         allColors = su.colorsCSS(len(speakerNames)+len(st.session_state.categories))
         speakerColors = allColors[:len(speakerNames)]
@@ -561,7 +642,8 @@ try:
         st.session_state.summaries[currFileIndex]["df4"] = df4
         
         with dataTab:
-            csv = convert_df(currDF)
+            displayDF = apply_speaker_renames_to_df(currDF, currFileIndex, column="Resource")
+            csv = convert_df(displayDF)
             
             st.download_button(
                "Press to Download analysis data",
@@ -571,7 +653,7 @@ try:
                key='download-csv',
                on_click="ignore",
             )
-            st.dataframe(currDF)
+            st.dataframe(displayDF)
         with pie1:
             printV("In Pie1",4)
             df3 = st.session_state.summaries[currFileIndex]["df3"]
@@ -585,46 +667,52 @@ try:
             printV("Pie1 Pretrace",4)
             fig1.add_trace(go.Pie(values=df3["values"],labels=df3["names"],sort=False))
             printV("Pie1 Posttrace",4)
-            
+            st.plotly_chart(fig1, use_container_width=True, config=config)
             col1_1, col1_2 = st.columns(2)
-            fig1.write_image("ascn_pie1.pdf")
-            fig1.write_image("ascn_pie1.svg")
+            try:
+                fig1.write_image("ascn_pie1.pdf")
+                fig1.write_image("ascn_pie1.svg")
+            except Exception:
+                pass
             printV("Pie1 files written",4)
             with col1_1:
-                printV("Pie1 in col1_1",4)
-                with open('ascn_pie1.pdf','rb') as f:
-                    printV("Pie1 in file open",4)
-                    st.download_button(
-                        "Save As PDF",
-                        f,
-                        'sonogram-voice-category-'+currPlainName+'.pdf',
-                        'application/pdf',
-                        key='download-pdf1',
-                        on_click="ignore",
-                    )
-                    printV("Pie1 after col1_1",4)
+                if os.path.exists('ascn_pie1.pdf'):
+                    printV("Pie1 in col1_1",4)
+                    with open('ascn_pie1.pdf','rb') as f:
+                        printV("Pie1 in file open",4)
+                        st.download_button(
+                            "Save As PDF",
+                            f,
+                            'sonogram-voice-category-'+currPlainName+'.pdf',
+                            'application/pdf',
+                            key='download-pdf1',
+                            on_click="ignore",
+                        )
+                        printV("Pie1 after col1_1",4)
             with col1_2:
-                with open('ascn_pie1.svg','rb') as f:
-                    st.download_button(
-                        "Save As SVG",
-                        f,
-                        'sonogram-voice-category-'+currPlainName+'.svg',
-                        'image/svg+xml',
-                        key='download-svg1',
-                        on_click="ignore",
-                    )
-                    printV("Pie1 in col1_2",4)
-            st.plotly_chart(fig1, use_container_width=True,config=config)
+                if os.path.exists('ascn_pie1.svg'):
+                    with open('ascn_pie1.svg','rb') as f:
+                        st.download_button(
+                            "Save As SVG",
+                            f,
+                            'sonogram-voice-category-'+currPlainName+'.svg',
+                            'image/svg+xml',
+                            key='download-svg1',
+                            on_click="ignore",
+                        )
+                        printV("Pie1 in col1_2",4)
             printV("Pie1 post plotly",4)
 
         with pie2:
-            df4 = st.session_state.summaries[currFileIndex]["df4"]
+            printV("In Pie2",4)
+            df4 = st.session_state.summaries[currFileIndex]["df4"].copy()
         
             # Some speakers may be missing, so fix colors
             figColors = []
             for n in df4["names"]:
                 if n in speakerNames:
                     figColors.append(speakerColors[speakerNames.index(n)])
+            df4["names"] = df4["names"].apply(lambda s: get_display_name(s, currFileIndex))
             fig2 = go.Figure()
             fig2.update_layout(
                 title_text="Percentage of Speakers and Custom Categories",
@@ -632,35 +720,43 @@ try:
                 plot_bgcolor='rgba(0, 0, 0, 0)',
                 paper_bgcolor='rgba(0, 0, 0, 0)',
             )
+            printV("Pie2 Pretrace",4)
             fig2.add_trace(go.Pie(values=df4["values"],labels=df4["names"],sort=False))
-
+            printV("Pie2 Posttrace",4)
+            st.plotly_chart(fig2, use_container_width=True, config=config)
             col2_1, col2_2 = st.columns(2)
-            fig2.write_image("ascn_pie2.pdf")
-            fig2.write_image("ascn_pie2.svg")
+            try:
+                fig2.write_image("ascn_pie2.pdf")
+                fig2.write_image("ascn_pie2.svg")
+            except Exception:
+                pass
             with col2_1:
-                with open('ascn_pie2.pdf','rb') as f:
-                    st.download_button(
-                        "Save As PDF",
-                        f,
-                        'sonogram-speaker-percent-'+currPlainName+'.pdf',
-                        'application/pdf',
-                        key='download-pdf2',
-                        on_click="ignore",
-                    )
+                if os.path.exists('ascn_pie2.pdf'):
+                    with open('ascn_pie2.pdf','rb') as f:
+                        st.download_button(
+                            "Save As PDF",
+                            f,
+                            'sonogram-speaker-percent-'+currPlainName+'.pdf',
+                            'application/pdf',
+                            key='download-pdf2',
+                            on_click="ignore",
+                        )
             with col2_2:
-                with open('ascn_pie2.svg','rb') as f:
-                    st.download_button(
-                        "Save As SVG",
-                        f,
-                        'sonogram-speaker-percent-'+currPlainName+'.svg',
-                        'image/svg+xml',
-                        key='download-svg2',
-                        on_click="ignore",
-                    )
-            st.plotly_chart(fig2, use_container_width=True,config=config)
+                if os.path.exists('ascn_pie2.svg'):
+                    with open('ascn_pie2.svg','rb') as f:
+                        st.download_button(
+                            "Save As SVG",
+                            f,
+                            'sonogram-speaker-percent-'+currPlainName+'.svg',
+                            'image/svg+xml',
+                            key='download-svg2',
+                            on_click="ignore",
+                        )
 
         with sunburst1:
-            df5 = st.session_state.summaries[currFileIndex]["df5"]
+            df5 = st.session_state.summaries[currFileIndex]["df5"].copy()
+            df5["labels"] = df5["labels"].apply(lambda s: get_display_name(s, currFileIndex))
+            df5["parentNames"] = df5["parentNames"].apply(lambda s: get_display_name(s, currFileIndex))
             fig3_1 = px.sunburst(df5,
                                 branchvalues = 'total',
                                 names = "labels",
@@ -685,34 +781,40 @@ try:
                 plot_bgcolor='rgba(0, 0, 0, 0)',
                 paper_bgcolor='rgba(0, 0, 0, 0)',
             )
-            
+            st.plotly_chart(fig3_1, use_container_width=True, config=config)
             col3_1, col3_2 = st.columns(2)
-            fig3_1.write_image("ascn_sunburst.pdf")
-            fig3_1.write_image("ascn_sunburst.svg")
+            try:
+                fig3_1.write_image("ascn_sunburst.pdf")
+                fig3_1.write_image("ascn_sunburst.svg")
+            except Exception:
+                pass
             with col3_1:
-                with open('ascn_sunburst.pdf','rb') as f:
-                    st.download_button(
-                        "Save As PDF",
-                        f,
-                        'sonogram-speaker-categories-'+currPlainName+'.pdf',
-                        'application/pdf',
-                        key='download-pdf3',
-                        on_click="ignore",
-                    )
+                if os.path.exists('ascn_sunburst.pdf'):
+                    with open('ascn_sunburst.pdf','rb') as f:
+                        st.download_button(
+                            "Save As PDF",
+                            f,
+                            'sonogram-speaker-categories-'+currPlainName+'.pdf',
+                            'application/pdf',
+                            key='download-pdf3',
+                            on_click="ignore",
+                        )
             with col3_2:
-                with open('ascn_sunburst.svg','rb') as f:
-                    st.download_button(
-                        "Save As SVG",
-                        f,
-                        'sonogram-speaker-categories-'+currPlainName+'.svg',
-                        'image/svg+xml',
-                        key='download-svg3',
-                        on_click="ignore",
-                    )
-            st.plotly_chart(fig3_1, use_container_width=True,config=config)
+                if os.path.exists('ascn_sunburst.svg'):
+                    with open('ascn_sunburst.svg','rb') as f:
+                        st.download_button(
+                            "Save As SVG",
+                            f,
+                            'sonogram-speaker-categories-'+currPlainName+'.svg',
+                            'image/svg+xml',
+                            key='download-svg3',
+                            on_click="ignore",
+                        )
     
         with treemap1:
-            df5 = st.session_state.summaries[currFileIndex]["df5"]
+            df5 = st.session_state.summaries[currFileIndex]["df5"].copy()
+            df5["labels"] = df5["labels"].apply(lambda s: get_display_name(s, currFileIndex))
+            df5["parentNames"] = df5["parentNames"].apply(lambda s: get_display_name(s, currFileIndex))
             fig3 = px.treemap(df5,
                             branchvalues = "total",
                             names = "labels",
@@ -737,37 +839,43 @@ try:
                 plot_bgcolor='rgba(0, 0, 0, 0)',
                 paper_bgcolor='rgba(0, 0, 0, 0)',
             )
-                        
+            st.plotly_chart(fig3, use_container_width=True, config=config)            
             col4_1, col4_2 = st.columns(2)
-            fig3.write_image("ascn_treemap.pdf")
-            fig3.write_image("ascn_treemap.svg")
+            try:
+                fig3.write_image("ascn_treemap.pdf")
+                fig3.write_image("ascn_treemap.svg")
+            except Exception:
+                pass
             with col4_1:
-                with open('ascn_treemap.pdf','rb') as f:
-                    st.download_button(
-                        "Save As PDF",
-                        f,
-                        'sonogram-treemap-'+currPlainName+'.pdf',
-                        'application/pdf',
-                        key='download-pdf4',
-                        on_click="ignore",
-                    )
+                if os.path.exists('ascn_treemap.pdf'):
+                    with open('ascn_treemap.pdf','rb') as f:
+                        st.download_button(
+                            "Save As PDF",
+                            f,
+                            'sonogram-treemap-'+currPlainName+'.pdf',
+                            'application/pdf',
+                            key='download-pdf4',
+                            on_click="ignore",
+                        )
             with col4_2:
-                with open('ascn_treemap.svg','rb') as f:
-                    st.download_button(
-                        "Save As SVG",
-                        f,
-                        'sonogram-treemap-'+currPlainName+'.svg',
-                        'image/svg+xml',
-                        key='download-svg4',
-                        on_click="ignore",
-                    )
-            st.plotly_chart(fig3, use_container_width=True,config=config)
+                if os.path.exists('ascn_treemap.svg'):
+                    with open('ascn_treemap.svg','rb') as f:
+                        st.download_button(
+                            "Save As SVG",
+                            f,
+                            'sonogram-treemap-'+currPlainName+'.svg',
+                            'image/svg+xml',
+                            key='download-svg4',
+                            on_click="ignore",
+                        )
        
         # generate plotting window
 
 
         with timeline:
-            fig_la = px.timeline(speakers_dataFrame, x_start="Start", x_end="Finish", y="Resource", color="Resource",title="Timeline of Audio with Speakers",
+            timeline_df = speakers_dataFrame.copy()
+            timeline_df["Resource"] = timeline_df["Resource"].apply(lambda s: get_display_name(s, currFileIndex))
+            fig_la = px.timeline(timeline_df, x_start="Start", x_end="Finish", y="Resource", color="Resource",title="Timeline of Audio with Speakers",
                                 color_discrete_sequence=speakerColors)
             fig_la.update_yaxes(autorange="reversed") 
             
@@ -793,34 +901,39 @@ try:
                 legend={'traceorder':'reversed'},
                 yaxis= {'showticklabels': False},
             )
-                                    
+            st.plotly_chart(fig_la, use_container_width=True, config=config)                        
             col5_1, col5_2 = st.columns(2)
-            fig_la.write_image("ascn_timeline.pdf")
-            fig_la.write_image("ascn_timeline.svg")
+            try:
+                fig_la.write_image("ascn_timeline.pdf")
+                fig_la.write_image("ascn_timeline.svg")
+            except Exception:
+                pass
             with col5_1:
-                with open('ascn_timeline.pdf','rb') as f:
-                    st.download_button(
-                        "Save As PDF",
-                        f,
-                        'sonogram-timeline-'+currPlainName+'.pdf',
-                        'application/pdf',
-                        key='download-pdf5',
-                        on_click="ignore",
-                    )
+                if os.path.exists('ascn_timeline.pdf'):
+                    with open('ascn_timeline.pdf','rb') as f:
+                        st.download_button(
+                            "Save As PDF",
+                            f,
+                            'sonogram-timeline-'+currPlainName+'.pdf',
+                            'application/pdf',
+                            key='download-pdf5',
+                            on_click="ignore",
+                        )
             with col5_2:
-                with open('ascn_timeline.svg','rb') as f:
-                    st.download_button(
-                        "Save As SVG",
-                        f,
-                        'sonogram-timeline-'+currPlainName+'.svg',
-                        'image/svg+xml',
-                        key='download-svg5',
-                        on_click="ignore",
-                    )
-            st.plotly_chart(fig_la, use_container_width=True,config=config)
+                if os.path.exists('ascn_timeline.svg'):
+                    with open('ascn_timeline.svg','rb') as f:
+                        st.download_button(
+                            "Save As SVG",
+                            f,
+                            'sonogram-timeline-'+currPlainName+'.svg',
+                            'image/svg+xml',
+                            key='download-svg5',
+                            on_click="ignore",
+                        )
     
         with bar1:
-            df2 = st.session_state.summaries[currFileIndex]["df2"]
+            df2 = st.session_state.summaries[currFileIndex]["df2"].copy()
+            df2["names"] = df2["names"].apply(lambda s: get_display_name(s, currFileIndex))
             fig2_la = px.bar(df2, x="values", y="names", color="names", orientation='h',
                             custom_data=["names","values"],title="Time Spoken by each Speaker",
                             color_discrete_sequence=catColors+speakerColors)
@@ -841,31 +954,35 @@ try:
                     'Percentage of Time: %{customdata[1]:.2f}%'
                 ])
             )
-                                                
+            st.plotly_chart(fig2_la, use_container_width=True, config=config)                                    
             col6_1, col6_2 = st.columns(2)
-            fig_la.write_image("ascn_bar.pdf")
-            fig_la.write_image("ascn_bar.svg")
+            try:
+                fig_la.write_image("ascn_bar.pdf")
+                fig_la.write_image("ascn_bar.svg")
+            except Exception:
+                pass
             with col6_1:
-                with open('ascn_bar.pdf','rb') as f:
-                    st.download_button(
-                        "Save As PDF",
-                        f,
-                        'sonogram-speaker-time-'+currPlainName+'.pdf',
-                        'application/pdf',
-                        key='download-pdf6',
-                        on_click="ignore",
-                    )
+                if os.path.exists('ascn_bar.pdf'):
+                    with open('ascn_bar.pdf','rb') as f:
+                        st.download_button(
+                            "Save As PDF",
+                            f,
+                            'sonogram-speaker-time-'+currPlainName+'.pdf',
+                            'application/pdf',
+                            key='download-pdf6',
+                            on_click="ignore",
+                        )
             with col6_2:
-                with open('ascn_bar.svg','rb') as f:
-                    st.download_button(
-                        "Save As SVG",
-                        f,
-                        'sonogram-speaker-time-'+currPlainName+'.svg',
-                        'image/svg+xml',
-                        key='download-svg6',
-                        on_click="ignore",
-                    )
-            st.plotly_chart(fig2_la, use_container_width=True,config=config)
+                if os.path.exists('ascn_bar.svg'):
+                    with open('ascn_bar.svg','rb') as f:
+                        st.download_button(
+                            "Save As SVG",
+                            f,
+                            'sonogram-speaker-time-'+currPlainName+'.svg',
+                            'image/svg+xml',
+                            key='download-svg6',
+                            on_click="ignore",
+                        )
 
 except ValueError:
     pass