diff --git a/bin/import_fisher.py b/bin/import_fisher.py
index 9a9a2eef..e4f95983 100755
--- a/bin/import_fisher.py
+++ b/bin/import_fisher.py
@@ -16,8 +16,8 @@ import os
 import pandas
 import subprocess
 import unicodedata
-import wave
-import audioop
+import librosa
+import resampy
 
 from util.text import validate_label
 
@@ -142,7 +142,7 @@ def _split_wav_and_sentences(data_dir, trans_data, original_data, converted_data
 
             print("splitting {} according to {}".format(wav_files, trans_file))
 
-            origAudios = [wave.open(wav_file, "r") for wav_file in wav_files]
+            origAudios = [librosa.load(wav_file, sr=None, mono=False) for wav_file in wav_files]
 
             # Loop over segments and split wav_file for each segment
             for segment in segments:
@@ -160,26 +160,20 @@ def _split_wav_and_sentences(data_dir, trans_data, original_data, converted_data
                 if transcript != None:
                     files.append((os.path.abspath(new_wav_file), new_wav_filesize, transcript))
 
-            # Close origAudios
-            for origAudio in origAudios:
-                origAudio.close()
-
     return pandas.DataFrame(data=files, columns=["wav_filename", "wav_filesize", "transcript"])
 
+def _split_audio(origAudio, start_time, stop_time):
+    audioData, frameRate = origAudio
+    nChannels = len(audioData.shape)
+    startIndex = int(start_time * frameRate)
+    stopIndex = int(stop_time * frameRate)
+    return audioData[startIndex: stopIndex] if 1 == nChannels else audioData[:, startIndex: stopIndex]
+
 def _split_and_resample_wav(origAudio, start_time, stop_time, new_wav_file):
-    nChannels = origAudio.getnchannels()
-    sampleWidth = origAudio.getsampwidth()
-    frameRate = origAudio.getframerate()
-    origAudio.setpos(int(start_time * frameRate))
-    chunkData = origAudio.readframes(int((stop_time - start_time) * frameRate))
-    # by doubling the frame-rate we effectively go from 8 kHz to 16 kHz
-    chunkData, _ = audioop.ratecv(chunkData, sampleWidth, nChannels, frameRate, 2 * frameRate, None)
-    chunkAudio = wave.open(new_wav_file, "w")
-    chunkAudio.setnchannels(nChannels)
-    chunkAudio.setsampwidth(sampleWidth)
-    chunkAudio.setframerate(2 * frameRate)
-    chunkAudio.writeframes(chunkData)
-    chunkAudio.close()
+    frameRate = origAudio[1]
+    chunkData = _split_audio(origAudio, start_time, stop_time)
+    chunkData = resampy.resample(chunkData, frameRate, 16000)
+    librosa.output.write_wav(new_wav_file, chunkData, 16000)
 
 def _split_sets(filelist):
     # We initially split the entire set into 80% train and 20% test, then
diff --git a/requirements.txt b/requirements.txt
index 8feeb860..22f03afd 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -15,3 +15,5 @@ requests
 tables
 attrdict
 setuptools
+librosa
+resampy