diff --git a/egs/speech_llm/SPEECH2SPEECH/qwen_omni/utils.py b/egs/speech_llm/SPEECH2SPEECH/qwen_omni/utils.py
index 81f7c0d5c..fad7f272c 100644
--- a/egs/speech_llm/SPEECH2SPEECH/qwen_omni/utils.py
+++ b/egs/speech_llm/SPEECH2SPEECH/qwen_omni/utils.py
@@ -430,46 +430,4 @@ def write_error_stats(
         hyp_count = corr + hyp_sub + ins
 
         print(f"{word}   {corr} {tot_errs} {ref_count} {hyp_count}", file=f)
-    return float(tot_err_rate)
-
-
-def get_dataset_statistics(dataset, save_filename):
-    speech_token_lengths = []
-    text_lengths = []
-    for item in tqdm(dataset):
-        if 'custom' not in item:
-            speech_token = item["code"]
-            text = item["text"]
-        else:
-            speech_token = item["custom"]["speech_token"]
-            text = item["supervisions"][0]["text"]
-        speech_token_lengths.append(len(speech_token))
-        text_lengths.append(len(text))
-    speech_token_length_array = np.array(speech_token_lengths)
-    text_length_array = np.array(text_lengths)
-    # 计算并存储统计指标
-    def get_length_stats(lengths_array):
-        length_stats = []
-        length_stats.append(["count", f"{len(lengths_array)}"]) # 总数
-        length_stats.append(["mean", f"{np.mean(lengths_array):.1f}"])
-        length_stats.append(["std", f"{np.std(lengths_array):.1f}"])
-        length_stats.append(["min", f"{np.min(lengths_array):.1f}"])
-        length_stats.append(["25%", f"{np.percentile(lengths_array, 25):.1f}"])
-        length_stats.append(["50% (median)", f"{np.median(lengths_array):.1f}"]) # median 和 50% percentile 是一样的
-        length_stats.append(["75%", f"{np.percentile(lengths_array, 75):.1f}"])
-        length_stats.append(["99%", f"{np.percentile(lengths_array, 99):.1f}"])
-        length_stats.append(["99.5%", f"{np.percentile(lengths_array, 99.5):.1f}"])
-        length_stats.append(["99.9%", f"{np.percentile(lengths_array, 99.9):.1f}"])
-        length_stats.append(["max", f"{np.max(lengths_array):.1f}"])
-        return length_stats
-    speech_length_stats = get_length_stats(speech_token_length_array)
-    text_length_stats = get_length_stats(text_length_array)
-    with open(save_filename, "w") as f:
-        print("speech_tokens 长度统计指标:", file=f)
-        for stat_name, stat_value in speech_length_stats:
-            print(f"{stat_name:<15}: {stat_value}", file=f)
-        print("\ntext 长度统计指标:", file=f)
-        for stat_name, stat_value in text_length_stats:
-            print(f"{stat_name:<15}: {stat_value}", file=f)
-
-    return speech_token_lengths, text_lengths
+    return float(tot_err_rate)
\ No newline at end of file