9. An apparatus for clustering a plurality of speech utterances into multiple clusters associated with multiple respective speakers, the apparatus comprising: a processor; and a memory with computer code instructions stored therein, the processor and the memory, with the computer code instructions, being configured to cause the apparatus to: define a clustering pattern having multiple clusters, each of the multiple clusters including at least one of the plurality of vector representations; iteratively, (1) evaluate a clustering confidence score in terms of silhouette width criterion values associated with at least a subset of the plurality of vector representations, the clustering confidence score representing a clustering validation metric, and (2) update the clustering pattern by merging a pair of nearest clusters, among clusters associated with the clustering pattern, into a single cluster, the pair of nearest clusters merged being determined based on a similarity score indicative of similarity between vector representations associated with different clusters; employ a modified silhouette width criterion function with a penalty term, the penalty term regularizing the silhouette width criterion values, the modified silhouette width criterion function enabling a stopping condition for the evaluating and updating; and provide an indication of a final clustering pattern to a speaker recognition engine, the final clustering pattern being determined as the clustering pattern corresponding to a highest value of the clustering confidence score, the final clustering pattern employed by the speaker recognition engine in associating speech utterances from at least one speaker of the multiple respective speakers with the at least one speaker.
9. An apparatus for clustering a plurality of speech utterances into multiple clusters associated with multiple respective speakers, the apparatus comprising: a processor; and a memory with computer code instructions stored therein, the processor and the memory, with the computer code instructions, being configured to cause the apparatus to: define a clustering pattern having multiple clusters, each of the multiple clusters including at least one of the plurality of vector representations; iteratively, (1) evaluate a clustering confidence score in terms of silhouette width criterion values associated with at least a subset of the plurality of vector representations, the clustering confidence score representing a clustering validation metric, and (2) update the clustering pattern by merging a pair of nearest clusters, among clusters associated with the clustering pattern, into a single cluster, the pair of nearest clusters merged being determined based on a similarity score indicative of similarity between vector representations associated with different clusters; employ a modified silhouette width criterion function with a penalty term, the penalty term regularizing the silhouette width criterion values, the modified silhouette width criterion function enabling a stopping condition for the evaluating and updating; and provide an indication of a final clustering pattern to a speaker recognition engine, the final clustering pattern being determined as the clustering pattern corresponding to a highest value of the clustering confidence score, the final clustering pattern employed by the speaker recognition engine in associating speech utterances from at least one speaker of the multiple respective speakers with the at least one speaker. 20. An apparatus according to claim 9 , wherein the processor and the memory, with the computer code instructions, are further configured to cause the apparatus to employ the final clustering pattern in speaker recognition by the speaker recognition engine.