diff --git a/examples/main/main.cpp b/examples/main/main.cpp
index b8366b79f4..105082cbaf 100644
--- a/examples/main/main.cpp
+++ b/examples/main/main.cpp
@@ -618,6 +618,8 @@ int main(int argc, char ** argv) {
fprintf(stderr, "%s: failed to process audio\n", argv[0]);
return 10;
}
+
+ whisper_full_cluster_segments(ctx);
}
// output stuff
diff --git a/whisper.cpp b/whisper.cpp
index 04cbc36b2c..4c208b9b49 100644
--- a/whisper.cpp
+++ b/whisper.cpp
@@ -603,6 +603,8 @@ struct whisper_context {
// [EXPERIMENTAL] speed-up techniques
int32_t exp_n_audio_ctx; // 0 - use default
+ std::vector<float> audio_embd;
+
void use_buf(struct ggml_context * ctx, int i) {
#if defined(WHISPER_USE_SCRATCH)
size_t last_size = 0;
@@ -1707,18 +1709,34 @@ static bool whisper_encode(
}
// cur
- //{
- // printf("ne0 = %d\n", cur->ne[0]);
- // printf("ne1 = %d\n", cur->ne[1]);
- // for (int i = 0; i < 10; ++i) {
- // printf("%8.4f ", ((float *)(cur->data))[i]);
- // }
- // printf("... ");
- // for (int i = cur->ne[0] - 10; i < cur->ne[0]; ++i) {
- // printf("%8.4f ", ((float *)(cur->data))[i]);
- // }
- // printf("\n");
- //}
+ {
+ //printf("ne0 = %d\n", cur->ne[0]);
+ //printf("ne1 = %d\n", cur->ne[1]);
+ //for (int i = 0; i < 10; ++i) {
+ // printf("%8.4f ", ((float *)(cur->data))[i]);
+ //}
+ //printf("... ");
+ //for (int i = cur->ne[0] - 10; i < cur->ne[0]; ++i) {
+ // printf("%8.4f ", ((float *)(cur->data))[i]);
+ //}
+ //printf("\n");
+ }
+
+ {
+ const int i0 = std::min(mel_offset, mel_inp.n_len);
+ const int i1 = std::min(mel_offset + 2*n_ctx, mel_inp.n_len);
+
+ printf("i0 = %d, i1 = %d, (i1 - i0) = %d, embd size = %d\n", i0, i1, i1 - i0, cur->ne[0]);
+
+ wctx.audio_embd.clear();
+ wctx.audio_embd.resize(cur->ne[0], 0.0f);
+ for (int j = 0; j < cur->ne[0]; ++j) {
+ for (int i = i0; i < i1; ++i) {
+ wctx.audio_embd[j] += ((float *)(cur->data))[(i - i0)*cur->ne[0] + j];
+ }
+ wctx.audio_embd[j] /= (i1 - i0);
+ }
+ }
// pre-compute cross-attention memory
{
@@ -4806,3 +4824,129 @@ static void whisper_exp_compute_token_level_timestamps(
// }
//}
}
+
+//
+// diarization stuff
+//
+
+void whisper_full_cluster_segments(struct whisper_context * ctx) {
+ const int n_segments = ctx->result_all.size();
+ printf("%s: clustering %d segments\n", __func__, n_segments);
+
+ const auto mel_len_save = ctx->mel.n_len;
+ printf("%s: mel_len_save = %d\n", __func__, mel_len_save);
+
+ std::vector<std::vector<float>> features(n_segments);
+
+ for (int i = 0; i < n_segments; ++i) {
+ const auto & segment_i = ctx->result_all[i];
+ printf("%s: segment %d: t0 = %d, t1 = %d, text = %s\n", __func__, i, (int) segment_i.t0, (int) segment_i.t1, segment_i.text.c_str());
+
+ ctx->mel.n_len = segment_i.t1;
+ whisper_encode(ctx, segment_i.t0, 4);
+
+ features[i] = ctx->audio_embd;
+ }
+
+ const int n_features = features[0].size();
+
+ // fuzzy c-means clustering
+ const int n_clusters = 4;
+
+ std::vector<std::vector<float>> centroids(n_clusters, std::vector<float>(n_features, 0.0));
+ std::vector<std::vector<float>> membership(n_segments, std::vector<float>(n_clusters, 0.0));
+
+ // initialize the centroids
+ for (int i = 0; i < n_clusters; ++i) {
+ for (int j = 0; j < n_features; ++j) {
+ centroids[i][j] = features[i][j];
+ }
+ }
+
+ // initialize the membership
+ for (int i = 0; i < n_segments; ++i) {
+ membership[i][i % n_clusters] = 1.0;
+ }
+
+ // iterate
+ for (int i = 0; i < 100; ++i) {
+ // update the centroids
+ for (int j = 0; j < n_clusters; ++j) {
+ for (int k = 0; k < n_features; ++k) {
+ centroids[j][k] = 0.0;
+ }
+ }
+
+ for (int j = 0; j < n_segments; ++j) {
+ for (int k = 0; k < n_clusters; ++k) {
+ for (int l = 0; l < n_features; ++l) {
+ centroids[k][l] += membership[j][k]*features[j][l];
+ }
+ }
+ }
+
+ for (int j = 0; j < n_clusters; ++j) {
+ float sum = 0.0;
+ for (int k = 0; k < n_segments; ++k) {
+ sum += membership[k][j];
+ }
+
+ for (int k = 0; k < n_features; ++k) {
+ centroids[j][k] /= sum;
+ }
+ }
+
+ // update the membership
+ for (int j = 0; j < n_segments; ++j) {
+ for (int k = 0; k < n_clusters; ++k) {
+ float sum = 0.0;
+ for (int l = 0; l < n_clusters; ++l) {
+ //sum += std::pow(whisper_distance(features[j], centroids[k])/whisper_distance(features[j], centroids[l]), 2.0/(2.0 - 1.0));
+
+ // use the euclidean distance
+ double d0 = 0.0;
+ for (int m = 0; m < n_features; ++m) {
+ d0 += std::pow(features[j][m] - centroids[k][m], 2.0);
+ }
+ d0 = std::sqrt(d0);
+
+ double d1 = 0.0;
+ for (int m = 0; m < n_features; ++m) {
+ d1 += std::pow(features[j][m] - centroids[l][m], 2.0);
+ }
+ d1 = std::sqrt(d1);
+ if (d1 == 0.0) {
+ sum += 1.0;
+ } else {
+ sum += std::pow(d0/d1, 2.0/(2.0 - 1.0));
+ }
+ }
+
+ membership[j][k] = 1.0/sum;
+ }
+ }
+
+ // print the membership
+ for (int i = 0; i < n_segments; ++i) {
+ printf("%s: membership %d: ", __func__, i);
+ for (int j = 0; j < n_clusters; ++j) {
+ printf("%f ", membership[i][j]);
+ }
+ printf(" '%s'\n", ctx->result_all[i].text.c_str());
+ }
+ printf("----------------\n");
+ }
+
+ // print the centroids
+ //for (int i = 0; i < n_clusters; ++i) {
+ // printf("%s: centroid %d: ", __func__, i);
+ // for (int j = 0; j < n_features; ++j) {
+ // printf("%f ", centroids[i][j]);
+ // }
+ // printf("\n");
+ //}
+
+ // restore the mel length
+ ctx->mel.n_len = mel_len_save;
+}
+
diff --git a/whisper.h b/whisper.h
index 7eece797c1..9e40e702c9 100644
--- a/whisper.h
+++ b/whisper.h
@@ -372,6 +372,10 @@ extern "C" {
WHISPER_API int whisper_bench_memcpy(int n_threads);
WHISPER_API int whisper_bench_ggml_mul_mat(int n_threads);
+ // Temporary experimental API
+
+ WHISPER_API void whisper_full_cluster_segments(struct whisper_context * ctx);
+
#ifdef __cplusplus
}
#endif